Spaces:

AryaWu
/

tokenmaxxing_trajectory_viewer

Running

App Files Files Community

tokenmaxxing_trajectory_viewer / graphs /all_transitions_python_qwen.html

Aryarya

build

4b4d08b 1 day ago

Raw

History Blame Contribute Delete

101 kB

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width,initial-scale=1">
	<title>Transition Probabilities — Merged Across Problems</title>
	<script src="https://unpkg.com/cytoscape@3.29.2/dist/cytoscape.min.js"></script>
	<style>
	* { box-sizing: border-box; margin: 0; padding: 0; }
	body { font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
	background: #f8fafc; color: #1e293b; font-size: 13px; }
	h1 { font-size: 1.3rem; font-weight: 700; }
	.page-header { padding: 16px 28px 10px; border-bottom: 1px solid #e2e8f0;
	background: white; display: flex; align-items: baseline; gap: 14px; flex-wrap: wrap; }
	.subtitle { font-size: 0.78rem; color: #64748b; }

	.main { display: flex; gap: 12px; align-items: flex-start; padding: 14px 28px; }
	.cy-wrap { flex: 1 1 auto; min-width: 0; border: 1px solid #e2e8f0; border-radius: 8px;
	background: white; overflow: hidden; }
	#cy { width: 100%; height: 700px; }
	.detail-panel { flex: 0 0 360px; border: 1px solid #e2e8f0; border-radius: 8px;
	background: white; padding: 12px; font-size: 0.75rem;
	height: 700px; overflow-y: auto; }
	.detail-placeholder { color: #94a3b8; font-style: italic; padding: 8px 0; }

	.det-title { font-weight: 700; margin-bottom: 8px; font-size: 0.9rem;
	display: flex; align-items: center; gap: 6px; flex-wrap: wrap; }
	.det-def { font-size: 0.72rem; color: #475569; margin-bottom: 8px; line-height: 1.45; }
	.det-row { display: flex; gap: 6px; margin-bottom: 3px; align-items: baseline; }
	.det-lbl { color: #64748b; min-width: 96px; flex-shrink: 0; font-size: 0.72rem; }
	.det-val { color: #1e293b; font-family: monospace; font-size: 0.78rem; }
	.state-chip { font-size: 0.74rem; font-weight: 700; color: white; padding: 2px 8px;
	border-radius: 4px; white-space: nowrap; }
	.det-sub { font-size: 0.68rem; font-weight: 700; color: #64748b; margin: 10px 0 5px;
	text-transform: uppercase; }

	/* breakdown bars */
	.bd-row { margin-bottom: 10px; }
	.bd-head { display: flex; justify-content: space-between; font-size: 0.72rem;
	gap: 6px; margin-bottom: 3px; align-items: flex-start; }
	.bd-lbl { font-weight: 600; flex: 1 1 auto; min-width: 0;
	display: flex; flex-wrap: wrap; gap: 2px; align-items: center; }
	.bd-num { font-family: monospace; color: #475569; flex-shrink: 0; }
	.bd-bar { height: 8px; border-radius: 4px; background: #eef2f7; overflow: hidden; }
	.bd-fill { height: 100%; border-radius: 4px; }
	.bd-ex { font-size: 0.64rem; font-family: ui-monospace, monospace; color: #64748b;
	padding: 2px 0 2px 6px; border-left: 2px solid #eef2f7; margin-top: 2px;
	white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
	.kind-pill { display: inline-block; font-size: 0.62rem; padding: 1px 6px; border-radius: 3px;
	font-family: ui-monospace, monospace; font-weight: 600; line-height: 1.4; }
	.kind-arrow { display: inline-block; color: #94a3b8; font-size: 0.7rem; margin: 0 1px; }

	/* gap label distribution bars */
	.lbl-row { margin-bottom: 7px; }
	.lbl-head { display: flex; justify-content: space-between; font-size: 0.72rem;
	gap: 6px; margin-bottom: 3px; align-items: center; }
	.lbl-pill { display: inline-block; font-size: 0.65rem; padding: 1px 7px; border-radius: 10px;
	font-weight: 700; white-space: nowrap; }
	.lbl-num { font-family: monospace; color: #475569; flex-shrink: 0; font-size: 0.7rem; }
	.lbl-bar { height: 8px; border-radius: 4px; background: #eef2f7; overflow: hidden; }
	.lbl-fill { height: 100%; border-radius: 4px; }

	/* outgoing distribution list (node detail) */
	.out-row { display: flex; align-items: center; gap: 6px; margin-bottom: 5px; }
	.out-tgt { width: 96px; flex-shrink: 0; font-size: 0.72rem; font-weight: 600; }
	.out-bar { flex: 1 1 auto; height: 10px; background: #eef2f7; border-radius: 5px; overflow: hidden; }
	.out-fill{ height: 100%; border-radius: 5px; }
	.out-num { width: 78px; flex-shrink: 0; text-align: right; font-family: monospace;
	font-size: 0.72rem; color: #475569; }

	/* NLP metric distribution bars */
	.nlp-row { display: flex; align-items: center; gap: 6px; margin-bottom: 4px; }
	.nlp-lbl { width: 140px; flex-shrink: 0; font-size: 0.7rem; color: #374151; }
	.nlp-bar { flex: 1 1 auto; height: 8px; background: #eef2f7; border-radius: 4px; overflow: hidden; }
	.nlp-fill{ height: 100%; border-radius: 4px; background: #6366f1; }
	.nlp-num { width: 44px; flex-shrink: 0; text-align: right; font-family: monospace;
	font-size: 0.7rem; color: #475569; }
	.nlp-chip { display: inline-block; font-size: 0.64rem; padding: 1px 6px; border-radius: 10px;
	font-weight: 700; background: #eef2ff; color: #4338ca; margin: 1px; white-space: nowrap; }

	.table-section { padding: 6px 28px 32px; }
	.table-section h2 { font-size: 0.95rem; margin-bottom: 8px; }
	table.verify { border-collapse: collapse; font-size: 0.74rem; }
	table.verify th, table.verify td { border: 1px solid #e2e8f0; padding: 4px 9px; text-align: center; }
	table.verify thead th { background: #f1f5f9; }
	table.verify td.tr-name { text-align: left; font-weight: 700; font-family: monospace; }
	table.verify td.tr-total { font-weight: 700; background: #f8fafc; font-family: monospace; }
	table.verify td.tr-sum { font-weight: 700; color: #16a34a; font-family: monospace; }
	</style>
	</head>
	<body>
	<div class="page-header">
	<h1>Transition Probabilities</h1>
	<span class="subtitle">python · qwen · 97 problems merged · edge label = count · click a node or edge for details</span>
	</div>

	<div class="main">
	<div class="cy-wrap"><div id="cy"></div></div>
	<div class="detail-panel" id="detail">
	<div class="detail-placeholder">Click a node or edge for details</div>
	</div>
	</div>

	<div class="table-section">
	<h2>Verification — outgoing probability per source state (sums to 100%)</h2>
	<table class="verify">
	<thead><tr><th class="tr-name" style="text-align:left">source</th><th>out total</th><th>Σ%</th>
	<th style="text-align:left">→ targets</th></tr></thead>
	<tbody><tr><td class="tr-name">start</td><td class="tr-total">97</td><td class="tr-sum">100%</td><td style="text-align:left">breakthrough <b>74.2%</b> <span style="color:#94a3b8">(72)</span>   improved <b>14.4%</b> <span style="color:#94a3b8">(14)</span>   stuck <b>11.3%</b> <span style="color:#94a3b8">(11)</span></td></tr><tr><td class="tr-name">improved</td><td class="tr-total">31</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>22.6%</b> <span style="color:#94a3b8">(7)</span>   regressed <b>19.4%</b> <span style="color:#94a3b8">(6)</span>   end_limit <b>19.4%</b> <span style="color:#94a3b8">(6)</span>   breakthrough <b>16.1%</b> <span style="color:#94a3b8">(5)</span>   churn <b>12.9%</b> <span style="color:#94a3b8">(4)</span>   broke <b>6.5%</b> <span style="color:#94a3b8">(2)</span>   improved <b>3.2%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">churn</td><td class="tr-total">21</td><td class="tr-sum">100%</td><td style="text-align:left">churn <b>47.6%</b> <span style="color:#94a3b8">(10)</span>   stuck <b>23.8%</b> <span style="color:#94a3b8">(5)</span>   end_limit <b>19.0%</b> <span style="color:#94a3b8">(4)</span>   breakthrough <b>4.8%</b> <span style="color:#94a3b8">(1)</span>   improved <b>4.8%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">stuck</td><td class="tr-total">42</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>38.1%</b> <span style="color:#94a3b8">(16)</span>   improved <b>21.4%</b> <span style="color:#94a3b8">(9)</span>   breakthrough <b>14.3%</b> <span style="color:#94a3b8">(6)</span>   end_limit <b>11.9%</b> <span style="color:#94a3b8">(5)</span>   churn <b>9.5%</b> <span style="color:#94a3b8">(4)</span>   broke <b>2.4%</b> <span style="color:#94a3b8">(1)</span>   regressed <b>2.4%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">breakthrough</td><td class="tr-total">87</td><td class="tr-sum">100%</td><td style="text-align:left">end_submit <b>85.1%</b> <span style="color:#94a3b8">(74)</span>   stay <b>10.3%</b> <span style="color:#94a3b8">(9)</span>   regressed <b>3.4%</b> <span style="color:#94a3b8">(3)</span>   broke <b>1.1%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">stay</td><td class="tr-total">13</td><td class="tr-sum">100%</td><td style="text-align:left">end_submit <b>53.8%</b> <span style="color:#94a3b8">(7)</span>   stay <b>30.8%</b> <span style="color:#94a3b8">(4)</span>   regressed <b>7.7%</b> <span style="color:#94a3b8">(1)</span>   end_limit <b>7.7%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">regressed</td><td class="tr-total">11</td><td class="tr-sum">100%</td><td style="text-align:left">breakthrough <b>27.3%</b> <span style="color:#94a3b8">(3)</span>   improved <b>27.3%</b> <span style="color:#94a3b8">(3)</span>   churn <b>27.3%</b> <span style="color:#94a3b8">(3)</span>   stuck <b>9.1%</b> <span style="color:#94a3b8">(1)</span>   broke <b>9.1%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">broke</td><td class="tr-total">5</td><td class="tr-sum">100%</td><td style="text-align:left">improved <b>60.0%</b> <span style="color:#94a3b8">(3)</span>   stuck <b>40.0%</b> <span style="color:#94a3b8">(2)</span></td></tr></tbody>
	</table>
	</div>

	<div class="table-section">
	<h2>Gap label distribution — for each label, which src→tgt edges carry it</h2>
	<table class="verify">
	<thead><tr><th class="tr-name" style="text-align:left">gap label</th><th>total</th>
	<th style="text-align:left">src→tgt breakdown</th></tr></thead>
	<tbody><tr><td class="tr-name">cosmetic_refactor</td><td class="tr-total">3</td><td style="text-align:left">improved→stuck <b>66.7%</b> <span style="color:#94a3b8">(2)</span>   breakthrough→stay <b>33.3%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">debug_failure</td><td class="tr-total">13</td><td style="text-align:left">stuck→stuck <b>30.8%</b> <span style="color:#94a3b8">(4)</span>   improved→end_limit <b>23.1%</b> <span style="color:#94a3b8">(3)</span>   broke→stuck <b>15.4%</b> <span style="color:#94a3b8">(2)</span>   stuck→end_limit <b>7.7%</b> <span style="color:#94a3b8">(1)</span>   improved→stuck <b>7.7%</b> <span style="color:#94a3b8">(1)</span>   churn→churn <b>7.7%</b> <span style="color:#94a3b8">(1)</span>   stay→end_limit <b>7.7%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">execute_plan</td><td class="tr-total">1</td><td style="text-align:left">broke→improved <b>100.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">explore</td><td class="tr-total">12</td><td style="text-align:left">stuck→stuck <b>25.0%</b> <span style="color:#94a3b8">(3)</span>   start→stuck <b>16.7%</b> <span style="color:#94a3b8">(2)</span>   improved→end_limit <b>16.7%</b> <span style="color:#94a3b8">(2)</span>   churn→end_limit <b>16.7%</b> <span style="color:#94a3b8">(2)</span>   stuck→end_limit <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   improved→stuck <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   improved→broke <b>8.3%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">fix_bug</td><td class="tr-total">44</td><td style="text-align:left">stuck→stuck <b>13.6%</b> <span style="color:#94a3b8">(6)</span>   stuck→improved <b>13.6%</b> <span style="color:#94a3b8">(6)</span>   improved→breakthrough <b>11.4%</b> <span style="color:#94a3b8">(5)</span>   stuck→breakthrough <b>9.1%</b> <span style="color:#94a3b8">(4)</span>   stay→stay <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   breakthrough→stay <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   regressed→improved <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   churn→churn <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   churn→stuck <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   stuck→churn <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   broke→improved <b>4.5%</b> <span style="color:#94a3b8">(2)</span>   regressed→breakthrough <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→regressed <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   improved→regressed <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   regressed→churn <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   churn→breakthrough <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   stuck→regressed <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   improved→improved <b>2.3%</b> <span style="color:#94a3b8">(1)</span>   churn→improved <b>2.3%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">implement</td><td class="tr-total">108</td><td style="text-align:left">start→breakthrough <b>66.7%</b> <span style="color:#94a3b8">(72)</span>   start→improved <b>13.0%</b> <span style="color:#94a3b8">(14)</span>   start→stuck <b>8.3%</b> <span style="color:#94a3b8">(9)</span>   breakthrough→stay <b>1.9%</b> <span style="color:#94a3b8">(2)</span>   churn→stuck <b>1.9%</b> <span style="color:#94a3b8">(2)</span>   stuck→stuck <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   regressed→breakthrough <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   improved→stuck <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   churn→churn <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→broke <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   stuck→improved <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   stuck→churn <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   stuck→broke <b>0.9%</b> <span style="color:#94a3b8">(1)</span>   improved→broke <b>0.9%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">optimize_perf</td><td class="tr-total">12</td><td style="text-align:left">improved→regressed <b>25.0%</b> <span style="color:#94a3b8">(3)</span>   stay→stay <b>16.7%</b> <span style="color:#94a3b8">(2)</span>   stuck→stuck <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   stay→regressed <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   regressed→breakthrough <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→stay <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→regressed <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   regressed→churn <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   regressed→broke <b>8.3%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">rewrite</td><td class="tr-total">25</td><td style="text-align:left">churn→churn <b>24.0%</b> <span style="color:#94a3b8">(6)</span>   improved→churn <b>16.0%</b> <span style="color:#94a3b8">(4)</span>   stuck→breakthrough <b>8.0%</b> <span style="color:#94a3b8">(2)</span>   improved→regressed <b>8.0%</b> <span style="color:#94a3b8">(2)</span>   improved→stuck <b>8.0%</b> <span style="color:#94a3b8">(2)</span>   stuck→improved <b>8.0%</b> <span style="color:#94a3b8">(2)</span>   stuck→stuck <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→stay <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→regressed <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   regressed→improved <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   regressed→churn <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   churn→stuck <b>4.0%</b> <span style="color:#94a3b8">(1)</span>   stuck→churn <b>4.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">verify</td><td class="tr-total">89</td><td style="text-align:left">breakthrough→end_submit <b>83.1%</b> <span style="color:#94a3b8">(74)</span>   stay→end_submit <b>7.9%</b> <span style="color:#94a3b8">(7)</span>   stuck→end_limit <b>3.4%</b> <span style="color:#94a3b8">(3)</span>   breakthrough→stay <b>2.2%</b> <span style="color:#94a3b8">(2)</span>   churn→end_limit <b>2.2%</b> <span style="color:#94a3b8">(2)</span>   improved→end_limit <b>1.1%</b> <span style="color:#94a3b8">(1)</span></td></tr></tbody>
	</table>
	</div>

	<script>
	const M = {"canvas": {"w": 760, "h": 760}, "nodes": [{"id": "start", "label": "▶", "state_type": "start", "color": "#9E9E9E", "definition": "Virtual starting state — before any solution.py was written.", "visits": 97, "out_total": 97, "nlp_out": {"m1_correctness": 81.4, "m2": 75.3, "m4": 22.7, "m1_efficiency": 44.3, "m6": 45.4, "m7": 7.2, "m3_existing": 20.6, "m1_clarity": 2.1, "m9": 8.2, "m8_lang": 4.1, "m3_sample": 1.0}, "nlp_out_total": 97, "nlp_in": {}, "nlp_in_total": 0, "gap_out": {"implement": 97.9, "explore": 2.1}, "gap_out_total": 97, "gap_in": {}, "gap_in_total": 0, "x": 80.0, "y": 380.0}, {"id": "improved", "label": "improved", "state_type": "improved", "color": "#2196F3", "definition": "Gained tests, lost none (but not yet all-pass).", "visits": 31, "out_total": 31, "nlp_out": {"m1_correctness": 87.1, "m2": 80.6, "m4": 16.1, "m3_existing": 54.8, "m7": 3.2, "m9": 32.3, "m6": 38.7, "m8_inline": 6.5, "m1_efficiency": 54.8, "m3_sample": 6.5, "m8_lang": 9.7}, "nlp_out_total": 31, "nlp_in": {"m1_correctness": 77.4, "m1_efficiency": 38.7, "m2": 87.1, "m4": 25.8, "m3_existing": 35.5, "m6": 38.7, "m9": 12.9, "m7": 3.2, "m8_lang": 6.5, "m3_sample": 9.7, "m3_own": 3.2, "m8_inline": 3.2}, "nlp_in_total": 31, "gap_out": {"rewrite": 25.8, "fix_bug": 22.6, "explore": 12.9, "debug_failure": 12.9, "optimize_perf": 9.7, "implement": 6.5, "cosmetic_refactor": 6.5, "verify": 3.2}, "gap_out_total": 31, "gap_in": {"implement": 48.4, "fix_bug": 38.7, "rewrite": 9.7, "execute_plan": 3.2}, "gap_in_total": 31, "x": 260.0, "y": 170.0}, {"id": "churn", "label": "churn", "state_type": "churn", "color": "#9C27B0", "definition": "Gained some tests AND lost others — mixed regression+improvement.", "visits": 21, "out_total": 21, "nlp_out": {"m1_correctness": 90.5, "m1_efficiency": 71.4, "m2": 90.5, "m6": 47.6, "m7": 9.5, "m8_inline": 14.3, "m3_existing": 47.6, "m9": 19.0, "m4": 14.3, "m8_lang": 4.8}, "nlp_out_total": 21, "nlp_in": {"m1_correctness": 90.5, "m1_efficiency": 81.0, "m2": 100.0, "m6": 42.9, "m4": 23.8, "m9": 14.3, "m7": 4.8, "m8_inline": 9.5, "m3_existing": 33.3, "m8_lang": 9.5}, "nlp_in_total": 21, "gap_out": {"rewrite": 33.3, "fix_bug": 28.6, "implement": 14.3, "explore": 9.5, "verify": 9.5, "debug_failure": 4.8}, "gap_out_total": 21, "gap_in": {"rewrite": 57.1, "fix_bug": 23.8, "implement": 9.5, "debug_failure": 4.8, "optimize_perf": 4.8}, "gap_in_total": 21, "x": 365.0, "y": 170.0}, {"id": "stuck", "label": "stuck", "state_type": "stuck", "color": "#FF9800", "definition": "Identical test tuple — no change from the previous snapshot.", "visits": 42, "out_total": 42, "nlp_out": {"m1_correctness": 71.4, "m2": 83.3, "m3_existing": 35.7, "m4": 19.0, "m9": 33.3, "m1_efficiency": 31.0, "m6": 26.2, "m3_sample": 11.9, "m3_own": 4.8, "m8_lang": 16.7, "m8_inline": 4.8}, "nlp_out_total": 42, "nlp_in": {"m1_correctness": 88.1, "m1_efficiency": 54.8, "m2": 85.7, "m3_existing": 33.3, "m4": 23.8, "m6": 21.4, "m8_lang": 4.8, "m9": 35.7, "m3_sample": 11.9, "m3_own": 2.4, "m8_inline": 4.8}, "nlp_in_total": 42, "gap_out": {"fix_bug": 45.2, "rewrite": 14.3, "debug_failure": 11.9, "explore": 9.5, "implement": 9.5, "verify": 7.1, "optimize_perf": 2.4}, "gap_out_total": 42, "gap_in": {"implement": 31.0, "fix_bug": 21.4, "debug_failure": 16.7, "explore": 14.3, "rewrite": 9.5, "cosmetic_refactor": 4.8, "optimize_perf": 2.4}, "gap_in_total": 42, "x": 260.0, "y": 380.0}, {"id": "breakthrough", "label": "breakthrough", "state_type": "breakthrough", "color": "#00BCD4", "definition": "Some failing → all passing.", "visits": 87, "out_total": 87, "nlp_out": {"m1_correctness": 92.0, "m1_efficiency": 16.1, "m2": 23.0, "m3_existing": 89.7, "m3_own": 1.1, "m9": 17.2, "m3_sample": 14.9, "m7": 2.3, "m8_inline": 1.1, "m6": 4.6, "m4": 2.3}, "nlp_out_total": 87, "nlp_in": {"m1_correctness": 75.9, "m2": 72.4, "m4": 18.4, "m1_efficiency": 35.6, "m6": 49.4, "m7": 9.2, "m3_existing": 24.1, "m1_clarity": 2.3, "m9": 6.9, "m8_lang": 3.4, "m8_inline": 3.4}, "nlp_in_total": 87, "gap_out": {"verify": 87.4, "fix_bug": 3.4, "implement": 3.4, "optimize_perf": 2.3, "rewrite": 2.3, "cosmetic_refactor": 1.1}, "gap_out_total": 87, "gap_in": {"implement": 83.9, "fix_bug": 12.6, "rewrite": 2.3, "optimize_perf": 1.1}, "gap_in_total": 87, "x": 260.0, "y": 590.0}, {"id": "stay", "label": "stay", "state_type": "stay", "color": "#4CAF50", "definition": "All-pass → all-pass (model rewrote a working solution).", "visits": 13, "out_total": 13, "nlp_out": {"m1_efficiency": 46.2, "m2": 76.9, "m1_correctness": 76.9, "m3_existing": 69.2, "m6": 23.1, "m9": 23.1, "m3_sample": 7.7, "m3_own": 7.7, "m8_inline": 7.7}, "nlp_out_total": 13, "nlp_in": {"m1_correctness": 53.8, "m1_efficiency": 30.8, "m2": 69.2, "m3_existing": 46.2, "m9": 30.8, "m4": 15.4, "m6": 23.1}, "nlp_in_total": 13, "gap_out": {"verify": 53.8, "optimize_perf": 23.1, "fix_bug": 15.4, "debug_failure": 7.7}, "gap_out_total": 13, "gap_in": {"fix_bug": 30.8, "optimize_perf": 23.1, "verify": 15.4, "implement": 15.4, "cosmetic_refactor": 7.7, "rewrite": 7.7}, "gap_in_total": 13, "x": 470.0, "y": 590.0}, {"id": "regressed", "label": "regressed", "state_type": "regressed", "color": "#F44336", "definition": "Lost tests, gained none (but not all-fail).", "visits": 11, "out_total": 11, "nlp_out": {"m1_efficiency": 81.8, "m2": 100.0, "m1_correctness": 63.6, "m6": 54.5, "m8_inline": 9.1, "m3_existing": 18.2, "m9": 18.2, "m7": 9.1, "m4": 18.2}, "nlp_out_total": 11, "nlp_in": {"m1_efficiency": 72.7, "m2": 100.0, "m1_correctness": 90.9, "m3_existing": 54.5, "m9": 45.5, "m6": 45.5, "m3_sample": 9.1, "m4": 18.2}, "nlp_in_total": 11, "gap_out": {"fix_bug": 45.5, "optimize_perf": 27.3, "rewrite": 18.2, "implement": 9.1}, "gap_out_total": 11, "gap_in": {"optimize_perf": 45.5, "rewrite": 27.3, "fix_bug": 27.3}, "gap_in_total": 11, "x": 470.0, "y": 170.0}, {"id": "broke", "label": "broke", "state_type": "broke", "color": "#7B0000", "definition": "Had some passing → zero passing (or compile/runtime failure).", "visits": 5, "out_total": 5, "nlp_out": {"m1_correctness": 80.0, "m2": 80.0, "m3_existing": 40.0, "m9": 20.0, "m4": 20.0, "m6": 20.0, "m3_sample": 40.0, "m1_efficiency": 20.0}, "nlp_out_total": 5, "nlp_in": {"m1_correctness": 80.0, "m1_efficiency": 100.0, "m2": 100.0, "m3_existing": 20.0, "m6": 40.0, "m7": 20.0, "m3_sample": 20.0}, "nlp_in_total": 5, "gap_out": {"debug_failure": 40.0, "fix_bug": 40.0, "execute_plan": 20.0}, "gap_out_total": 5, "gap_in": {"implement": 60.0, "optimize_perf": 20.0, "explore": 20.0}, "gap_in_total": 5, "x": 470.0, "y": 380.0}, {"id": "end_submit", "label": "SUBMIT", "state_type": "end_submit", "color": "#607D8B", "definition": "Model submitted itself (ran COMPLETE_TASK_AND_SUBMIT_FINAL_OUTPUT).", "visits": 81, "out_total": 0, "nlp_out": {}, "nlp_out_total": 0, "nlp_in": {"m1_correctness": 96.3, "m1_efficiency": 13.6, "m2": 18.5, "m3_existing": 96.3, "m3_own": 2.5, "m9": 14.8, "m3_sample": 17.3, "m7": 1.2, "m8_inline": 1.2, "m6": 1.2}, "nlp_in_total": 81, "gap_out": {}, "gap_out_total": 0, "gap_in": {"verify": 100.0}, "gap_in_total": 81, "x": 680.0, "y": 290.0}, {"id": "end_limit", "label": "LIMIT", "state_type": "end_limit", "color": "#455A64", "definition": "Model force-stopped at the turn limit / wall-clock timeout.", "visits": 16, "out_total": 0, "nlp_out": {}, "nlp_out_total": 0, "nlp_in": {"m1_correctness": 68.8, "m1_efficiency": 43.8, "m2": 62.5, "m6": 43.8, "m8_lang": 37.5, "m9": 50.0, "m3_existing": 56.2, "m7": 6.2, "m8_inline": 6.2}, "nlp_in_total": 16, "gap_out": {}, "gap_out_total": 0, "gap_in": {"verify": 37.5, "explore": 31.2, "debug_failure": 31.2}, "gap_in_total": 16, "x": 680.0, "y": 470.0}], "edges": [{"id": "m0", "source": "start", "target": "breakthrough", "color": "#9E9E9E", "count": 72, "out_pct": 74.2, "label": "72", "n_unique_chains": 8, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 57, "pct": 79.2, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/1883/1883_B", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc302/abc302_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc303/abc303_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc305/abc305_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc305/abc305_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc308/abc308_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc310/abc310_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc312/abc312_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc315/abc315_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc318/abc318_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc319/abc319_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc322/abc322_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc325/abc325_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc326/abc326_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc329/abc329_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc330/abc330_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc332/abc332_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc334/abc334_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc334/abc334_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc335/abc335_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc336/abc336_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc341/abc341_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc341/abc341_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc342/abc342_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc344/abc344_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc354/abc354_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc355/abc355_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc356/abc356_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc357/abc357_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc357/abc357_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc358/abc358_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc358/abc358_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc359/abc359_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc359/abc359_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc360/abc360_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc366/abc366_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc371/abc371_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc372/abc372_a", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "write"], "label": "inspect test file → inspect test file → write solution.py", "count": 6, "pct": 8.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc311/abc311_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc312/abc312_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc333/abc333_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc340/abc340_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc384/abc384_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_e", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 4, "pct": 5.6, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc302/abc302_c", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc333/abc333_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc308/abc308_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc395/abc395_c", "snap_from": -1, "snap_to": 0}]}, {"chain": ["write_script", "write_script", "write"], "label": "write helper script → write helper script → write solution.py", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc397/abc397_e", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "inspect", "inspect", "wc", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → inspect test file → wc (output size) → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc191/arc191_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["write_script", "write"], "label": "write helper script → write solution.py", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc193/arc193_a", "snap_from": -1, "snap_to": 0}]}], "label_dist": [{"label": "implement", "count": 72, "pct": 100.0}], "n_labeled": 72, "nlp_rates": {"m1_correctness": 78, "m2": 71, "m4": 17, "m1_efficiency": 40, "m6": 53, "m7": 10, "m3_existing": 18, "m1_clarity": 3, "m9": 3, "m8_lang": 3}}, {"id": "m1", "source": "breakthrough", "target": "end_submit", "color": "#00BCD4", "count": 74, "out_pct": 85.1, "label": "74", "n_unique_chains": 9, "breakdown": [{"chain": ["test", "submit"], "label": "run ./test.sh → submit", "count": 62, "pct": 83.8, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc302/abc302_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc302/abc302_c", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc303/abc303_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc305/abc305_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc305/abc305_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc308/abc308_d", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc310/abc310_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc310/abc310_f", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc312/abc312_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc312/abc312_d", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc313/abc313_a", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc315/abc315_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc318/abc318_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc319/abc319_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc322/abc322_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 8, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc325/abc325_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc326/abc326_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc329/abc329_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc330/abc330_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc332/abc332_c", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc333/abc333_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc333/abc333_c", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc334/abc334_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc334/abc334_c", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc335/abc335_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc336/abc336_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc340/abc340_c", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc341/abc341_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc342/abc342_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc344/abc344_d", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc351/abc351_a", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc354/abc354_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc355/abc355_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc357/abc357_b", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc357/abc357_d", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc358/abc358_a", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc358/abc358_e", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc359/abc359_c", "snap_from": 0, "snap_to": -1}]}, {"chain": ["run_sample", "test", "submit"], "label": "run solution.py (sample) → run ./test.sh → submit", "count": 3, "pct": 4.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/1883/1883_B", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc354/abc354_d", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_e", "snap_from": 0, "snap_to": -1}]}, {"chain": ["test", "test", "submit"], "label": "run ./test.sh → run ./test.sh → submit", "count": 2, "pct": 2.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc308/abc308_e", "snap_from": 0, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc381/abc381_e", "snap_from": 0, "snap_to": -1}]}, {"chain": ["submit"], "label": "submit", "count": 2, "pct": 2.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 5, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 5, "snap_to": -1}]}, {"chain": ["inspect", "inspect", "inspect", "test", "submit"], "label": "inspect test file → inspect test file → inspect test file → run ./test.sh → submit", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc311/abc311_d", "snap_from": 0, "snap_to": -1}]}, {"chain": ["inline_script", "test", "submit"], "label": "inline_script → run ./test.sh → submit", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": 4, "snap_to": -1}]}, {"chain": ["inspect", "test", "submit"], "label": "inspect test file → run ./test.sh → submit", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc365/abc365_d", "snap_from": 2, "snap_to": -1}]}, {"chain": ["run_sample", "run_sample", "test", "submit"], "label": "run solution.py (sample) → run solution.py (sample) → run ./test.sh → submit", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc383/abc383_c", "snap_from": 1, "snap_to": -1}]}, {"chain": ["inspect", "inspect", "inspect", "run_sample", "run_sample", "test", "submit"], "label": "inspect test file → inspect test file → inspect test file → run solution.py (sample) → run solution.py (sample) → run ./test.sh → submit", "count": 1, "pct": 1.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc393/abc393_e", "snap_from": 0, "snap_to": -1}]}], "label_dist": [{"label": "verify", "count": 74, "pct": 100.0}], "n_labeled": 74, "nlp_rates": {"m1_correctness": 96, "m1_efficiency": 11, "m2": 15, "m3_existing": 97, "m3_own": 1, "m9": 15, "m3_sample": 18, "m7": 1, "m8_inline": 1, "m6": 1}}, {"id": "m2", "source": "start", "target": "stuck", "color": "#9E9E9E", "count": 11, "out_pct": 11.3, "label": "11", "n_unique_chains": 5, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 7, "pct": 63.6, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc351/abc351_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc354/abc354_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc365/abc365_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc382/abc382_g", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc184/arc184_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 9.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc301/abc301_f", "snap_from": -1, "snap_to": 0}]}, {"chain": ["write_script", "write_script", "write"], "label": "write helper script → write helper script → write solution.py", "count": 1, "pct": 9.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": -1, "snap_to": 0}]}, {"chain": ["write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write"], "label": "write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write solution.py", "count": 1, "pct": 9.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["write", "write"], "label": "write solution.py → write solution.py", "count": 1, "pct": 9.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc195/arc195_d", "snap_from": -1, "snap_to": 0}]}], "label_dist": [{"label": "implement", "count": 9, "pct": 81.8}, {"label": "explore", "count": 2, "pct": 18.2}], "n_labeled": 11, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 64, "m2": 91, "m3_existing": 9, "m4": 55, "m6": 9, "m8_lang": 18, "m9": 36, "m3_sample": 9}}, {"id": "m3", "source": "stuck", "target": "stuck", "color": "#FF9800", "count": 16, "out_pct": 38.1, "label": "16", "n_unique_chains": 4, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 11, "pct": 68.8, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc301/abc301_f", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc301/abc301_f", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/abc301/abc301_f", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/abc382/abc382_g", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 7, "snap_to": 8}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 8, "snap_to": 9}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc195/arc195_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc195/arc195_d", "snap_from": 1, "snap_to": 2}]}, {"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 3, "pct": 18.8, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc365/abc365_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 5, "snap_to": 6}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 10, "snap_to": 11}]}, {"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 1, "pct": 6.2, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 6, "snap_to": 7}]}, {"chain": ["inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 6.2, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 9, "snap_to": 10}]}], "label_dist": [{"label": "fix_bug", "count": 6, "pct": 37.5}, {"label": "debug_failure", "count": 4, "pct": 25.0}, {"label": "explore", "count": 3, "pct": 18.8}, {"label": "implement", "count": 1, "pct": 6.2}, {"label": "optimize_perf", "count": 1, "pct": 6.2}, {"label": "rewrite", "count": 1, "pct": 6.2}], "n_labeled": 16, "nlp_rates": {"m1_correctness": 81, "m2": 88, "m3_existing": 38, "m4": 12, "m9": 50, "m1_efficiency": 44, "m6": 19, "m3_sample": 19, "m3_own": 6}}, {"id": "m4", "source": "stuck", "target": "end_limit", "color": "#FF9800", "count": 5, "out_pct": 11.9, "label": "5", "n_unique_chains": 3, "breakdown": [{"chain": [], "label": "(no useful command)", "count": 3, "pct": 60.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc301/abc301_f", "snap_from": 3, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/arc195/arc195_d", "snap_from": 2, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 5, "snap_to": -1}]}, {"chain": ["write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script"], "label": "write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc382/abc382_g", "snap_from": 1, "snap_to": -1}]}, {"chain": ["write_script"], "label": "write helper script", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 9, "snap_to": -1}]}], "label_dist": [{"label": "verify", "count": 3, "pct": 60.0}, {"label": "explore", "count": 1, "pct": 20.0}, {"label": "debug_failure", "count": 1, "pct": 20.0}], "n_labeled": 5, "nlp_rates": {"m1_correctness": 40, "m1_efficiency": 20, "m2": 40, "m6": 20, "m8_lang": 40, "m9": 40}}, {"id": "m5", "source": "start", "target": "improved", "color": "#9E9E9E", "count": 14, "out_pct": 14.4, "label": "14", "n_unique_chains": 5, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 8, "pct": 57.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc310/abc310_f", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc313/abc313_a", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_b", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_e", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc192/arc192_b", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "write"], "label": "inspect test file → inspect test file → write solution.py", "count": 3, "pct": 21.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": -1, "snap_to": 0}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "test", "inspect", "inspect", "inspect", "wc", "write"], "label": "inspect test file → inspect test file → run ./test.sh → inspect test file → inspect test file → inspect test file → wc (output size) → write solution.py", "count": 1, "pct": 7.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc337/abc337_e", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 7.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": -1, "snap_to": 0}]}, {"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 1, "pct": 7.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc383/abc383_c", "snap_from": -1, "snap_to": 0}]}], "label_dist": [{"label": "implement", "count": 14, "pct": 100.0}], "n_labeled": 14, "nlp_rates": {"m1_correctness": 86, "m1_efficiency": 50, "m2": 86, "m4": 29, "m3_existing": 43, "m6": 36, "m9": 14}}, {"id": "m6", "source": "improved", "target": "breakthrough", "color": "#2196F3", "count": 5, "out_pct": 16.1, "label": "5", "n_unique_chains": 5, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc310/abc310_f", "snap_from": 0, "snap_to": 1}]}, {"chain": ["test", "inspect", "write"], "label": "run ./test.sh → inspect test file → write solution.py", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc313/abc313_a", "snap_from": 0, "snap_to": 1}]}, {"chain": ["run_sample", "write"], "label": "run solution.py (sample) → write solution.py", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc383/abc383_c", "snap_from": 0, "snap_to": 1}]}, {"chain": ["inline_script", "inline_script", "inline_script", "inline_script", "write"], "label": "inline_script → inline_script → inline_script → inline_script → write solution.py", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 4, "snap_to": 5}]}, {"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 1, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_b", "snap_from": 0, "snap_to": 1}]}], "label_dist": [{"label": "fix_bug", "count": 5, "pct": 100.0}], "n_labeled": 5, "nlp_rates": {"m1_correctness": 80, "m2": 60, "m4": 20, "m3_existing": 80, "m7": 20, "m9": 40, "m6": 40, "m8_inline": 20}}, {"id": "m7", "source": "breakthrough", "target": "stay", "color": "#00BCD4", "count": 9, "out_pct": 10.3, "label": "9", "n_unique_chains": 4, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 6, "pct": 66.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc341/abc341_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc356/abc356_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_e", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc397/abc397_e", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/arc193/arc193_a", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_b", "snap_from": 0, "snap_to": 1}]}, {"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 1, "pct": 11.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 0, "snap_to": 1}]}, {"chain": ["test", "inspect", "write"], "label": "run ./test.sh → inspect test file → write solution.py", "count": 1, "pct": 11.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc392/abc392_b", "snap_from": 0, "snap_to": 1}]}, {"chain": ["inspect", "inspect", "inspect", "wc", "write"], "label": "inspect test file → inspect test file → inspect test file → wc (output size) → write solution.py", "count": 1, "pct": 11.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc191/arc191_d", "snap_from": 0, "snap_to": 1}]}], "label_dist": [{"label": "verify", "count": 2, "pct": 22.2}, {"label": "fix_bug", "count": 2, "pct": 22.2}, {"label": "implement", "count": 2, "pct": 22.2}, {"label": "optimize_perf", "count": 1, "pct": 11.1}, {"label": "cosmetic_refactor", "count": 1, "pct": 11.1}, {"label": "rewrite", "count": 1, "pct": 11.1}], "n_labeled": 9, "nlp_rates": {"m1_correctness": 56, "m1_efficiency": 22, "m2": 56, "m3_existing": 44, "m9": 33, "m4": 22, "m6": 11}}, {"id": "m8", "source": "stay", "target": "stay", "color": "#4CAF50", "count": 4, "out_pct": 30.8, "label": "4", "n_unique_chains": 3, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 50.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 2, "snap_to": 3}]}, {"chain": ["test", "run_sample", "write"], "label": "run ./test.sh → run solution.py (sample) → write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc392/abc392_b", "snap_from": 1, "snap_to": 2}]}, {"chain": ["run_sample", "inspect", "wc", "inspect", "run_sample", "test", "run_sample", "write"], "label": "run solution.py (sample) → inspect test file → wc (output size) → inspect test file → run solution.py (sample) → run ./test.sh → run solution.py (sample) → write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc392/abc392_b", "snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "optimize_perf", "count": 2, "pct": 50.0}, {"label": "fix_bug", "count": 2, "pct": 50.0}], "n_labeled": 4, "nlp_rates": {"m1_efficiency": 50, "m2": 100, "m1_correctness": 50, "m3_existing": 50, "m6": 50, "m9": 25}}, {"id": "m9", "source": "stay", "target": "regressed", "color": "#4CAF50", "count": 1, "out_pct": 7.7, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "optimize_perf", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_efficiency": 100, "m2": 100}}, {"id": "m10", "source": "regressed", "target": "breakthrough", "color": "#F44336", "count": 3, "out_pct": 27.3, "label": "3", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 3, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 4, "snap_to": 5}, {"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": 3, "snap_to": 4}, {"problem": "qwen3p6_35b_a3b_fp8/abc397/abc397_e", "snap_from": 1, "snap_to": 2}]}], "label_dist": [{"label": "optimize_perf", "count": 1, "pct": 33.3}, {"label": "fix_bug", "count": 1, "pct": 33.3}, {"label": "implement", "count": 1, "pct": 33.3}], "n_labeled": 3, "nlp_rates": {"m1_efficiency": 67, "m2": 100, "m1_correctness": 33, "m6": 33}}, {"id": "m11", "source": "breakthrough", "target": "regressed", "color": "#00BCD4", "count": 3, "out_pct": 3.4, "label": "3", "n_unique_chains": 2, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 66.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/abc397/abc397_e", "snap_from": 0, "snap_to": 1}]}, {"chain": ["inspect", "inspect", "write"], "label": "inspect test file → inspect test file → write solution.py", "count": 1, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 5, "snap_to": 6}]}], "label_dist": [{"label": "optimize_perf", "count": 1, "pct": 33.3}, {"label": "rewrite", "count": 1, "pct": 33.3}, {"label": "fix_bug", "count": 1, "pct": 33.3}], "n_labeled": 3, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m3_existing": 33, "m9": 33, "m6": 33}}, {"id": "m12", "source": "regressed", "target": "stuck", "color": "#F44336", "count": 1, "out_pct": 9.1, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["inline_script", "write"], "label": "inline_script → write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 6, "snap_to": 7}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m6": 100, "m8_inline": 100}}, {"id": "m13", "source": "stuck", "target": "breakthrough", "color": "#FF9800", "count": 6, "out_pct": 14.3, "label": "6", "n_unique_chains": 6, "breakdown": [{"chain": ["inline_script", "inline_script", "inline_script", "inline_script", "write"], "label": "inline_script → inline_script → inline_script → inline_script → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc324/abc324_d", "snap_from": 7, "snap_to": 8}]}, {"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": 1, "snap_to": 2}]}, {"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc351/abc351_a", "snap_from": 0, "snap_to": 1}]}, {"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc354/abc354_d", "snap_from": 0, "snap_to": 1}]}, {"chain": ["test", "inspect", "write"], "label": "run ./test.sh → inspect test file → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc365/abc365_d", "snap_from": 1, "snap_to": 2}]}, {"chain": ["inspect", "run_sample", "write_script", "write_script", "write"], "label": "inspect test file → run solution.py (sample) → write helper script → write helper script → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 4, "snap_to": 5}]}], "label_dist": [{"label": "fix_bug", "count": 4, "pct": 66.7}, {"label": "rewrite", "count": 2, "pct": 33.3}], "n_labeled": 6, "nlp_rates": {"m1_correctness": 67, "m2": 83, "m8_inline": 17, "m3_existing": 67, "m9": 33, "m4": 33, "m6": 17, "m8_lang": 17}}, {"id": "m14", "source": "improved", "target": "regressed", "color": "#2196F3", "count": 6, "out_pct": 19.4, "label": "6", "n_unique_chains": 4, "breakdown": [{"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 2, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 0, "snap_to": 1}]}, {"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 2, "snap_to": 3}]}, {"chain": ["inspect", "inspect", "inspect", "inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc337/abc337_e", "snap_from": 0, "snap_to": 1}]}, {"chain": ["run_sample", "run_sample", "write"], "label": "run solution.py (sample) → run solution.py (sample) → write solution.py", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 0, "snap_to": 1}]}], "label_dist": [{"label": "optimize_perf", "count": 3, "pct": 50.0}, {"label": "rewrite", "count": 2, "pct": 33.3}, {"label": "fix_bug", "count": 1, "pct": 16.7}], "n_labeled": 6, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m3_existing": 67, "m6": 50, "m1_efficiency": 67, "m9": 50, "m3_sample": 17, "m4": 17}}, {"id": "m15", "source": "regressed", "target": "improved", "color": "#F44336", "count": 3, "out_pct": 27.3, "label": "3", "n_unique_chains": 3, "breakdown": [{"chain": ["test", "inspect", "inspect", "write"], "label": "run ./test.sh → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc337/abc337_e", "snap_from": 1, "snap_to": 2}]}, {"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 1, "snap_to": 2}]}, {"chain": ["inspect", "inspect", "write"], "label": "inspect test file → inspect test file → write solution.py", "count": 1, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "fix_bug", "count": 2, "pct": 66.7}, {"label": "rewrite", "count": 1, "pct": 33.3}], "n_labeled": 3, "nlp_rates": {"m1_correctness": 67, "m2": 100, "m3_existing": 67, "m6": 100, "m9": 33, "m1_efficiency": 67, "m7": 33, "m4": 33}}, {"id": "m16", "source": "improved", "target": "end_limit", "color": "#2196F3", "count": 6, "out_pct": 19.4, "label": "6", "n_unique_chains": 6, "breakdown": [{"chain": ["inspect", "wc"], "label": "inspect test file → wc (output size)", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc337/abc337_e", "snap_from": 2, "snap_to": -1}]}, {"chain": ["test", "inspect", "inspect"], "label": "run ./test.sh → inspect test file → inspect test file", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 12, "snap_to": -1}]}, {"chain": [], "label": "(no useful command)", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 6, "snap_to": -1}]}, {"chain": ["run_sample", "write_script", "write_script", "inspect", "inspect", "write_script", "write_script", "inspect", "inspect", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script"], "label": "run solution.py (sample) → write helper script → write helper script → inspect test file → inspect test file → write helper script → write helper script → inspect test file → inspect test file → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc184/arc184_d", "snap_from": 1, "snap_to": -1}]}, {"chain": ["test", "inspect", "inspect", "inspect", "inspect", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script"], "label": "run ./test.sh → inspect test file → inspect test file → inspect test file → inspect test file → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc192/arc192_b", "snap_from": 0, "snap_to": -1}]}, {"chain": ["write_script", "test", "test", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script", "write_script"], "label": "write helper script → run ./test.sh → run ./test.sh → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script → write helper script", "count": 1, "pct": 16.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_d", "snap_from": 2, "snap_to": -1}]}], "label_dist": [{"label": "debug_failure", "count": 3, "pct": 50.0}, {"label": "explore", "count": 2, "pct": 33.3}, {"label": "verify", "count": 1, "pct": 16.7}], "n_labeled": 6, "nlp_rates": {"m1_correctness": 83, "m1_efficiency": 67, "m2": 83, "m3_existing": 83, "m6": 67, "m9": 67, "m8_lang": 50}}, {"id": "m17", "source": "stay", "target": "end_submit", "color": "#4CAF50", "count": 7, "out_pct": 53.8, "label": "7", "n_unique_chains": 3, "breakdown": [{"chain": ["test", "submit"], "label": "run ./test.sh → submit", "count": 5, "pct": 71.4, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc341/abc341_d", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc356/abc356_d", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_e", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/arc193/arc193_a", "snap_from": 1, "snap_to": -1}, {"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_b", "snap_from": 1, "snap_to": -1}]}, {"chain": ["submit"], "label": "submit", "count": 1, "pct": 14.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc397/abc397_e", "snap_from": 3, "snap_to": -1}]}, {"chain": ["inspect", "inspect", "test", "submit"], "label": "inspect test file → inspect test file → run ./test.sh → submit", "count": 1, "pct": 14.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc191/arc191_d", "snap_from": 1, "snap_to": -1}]}], "label_dist": [{"label": "verify", "count": 7, "pct": 100.0}], "n_labeled": 7, "nlp_rates": {"m1_correctness": 100, "m3_existing": 86, "m3_sample": 14, "m2": 57, "m1_efficiency": 43, "m3_own": 14, "m9": 14}}, {"id": "m18", "source": "improved", "target": "stuck", "color": "#2196F3", "count": 7, "out_pct": 22.6, "label": "7", "n_unique_chains": 2, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 6, "pct": 85.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc345/abc345_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 3, "snap_to": 4}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 5, "snap_to": 6}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 8, "snap_to": 9}, {"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_e", "snap_from": 0, "snap_to": 1}]}, {"chain": ["inspect", "inspect", "time", "run_sample", "run_sample", "write"], "label": "inspect test file → inspect test file → time solution.py → run solution.py (sample) → run solution.py (sample) → write solution.py", "count": 1, "pct": 14.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 4, "snap_to": 5}]}], "label_dist": [{"label": "cosmetic_refactor", "count": 2, "pct": 28.6}, {"label": "rewrite", "count": 2, "pct": 28.6}, {"label": "implement", "count": 1, "pct": 14.3}, {"label": "debug_failure", "count": 1, "pct": 14.3}, {"label": "explore", "count": 1, "pct": 14.3}], "n_labeled": 7, "nlp_rates": {"m1_correctness": 86, "m1_efficiency": 57, "m2": 57, "m3_existing": 43, "m9": 14, "m3_sample": 14, "m8_inline": 14, "m4": 14, "m6": 29}}, {"id": "m19", "source": "regressed", "target": "churn", "color": "#F44336", "count": 3, "out_pct": 27.3, "label": "3", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 3, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 3, "snap_to": 4}, {"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 1, "snap_to": 2}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 33.3}, {"label": "optimize_perf", "count": 1, "pct": 33.3}, {"label": "rewrite", "count": 1, "pct": 33.3}], "n_labeled": 3, "nlp_rates": {"m1_correctness": 67, "m1_efficiency": 100, "m2": 100, "m6": 33, "m4": 33, "m9": 33}}, {"id": "m20", "source": "churn", "target": "churn", "color": "#9C27B0", "count": 10, "out_pct": 47.6, "label": "10", "n_unique_chains": 4, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 6, "pct": 60.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 4, "snap_to": 5}, {"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 5, "snap_to": 6}, {"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 6, "snap_to": 7}, {"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 9, "snap_to": 10}, {"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": 3, "snap_to": 4}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 6, "snap_to": 7}]}, {"chain": ["inline_script", "write"], "label": "inline_script → write solution.py", "count": 2, "pct": 20.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 7, "snap_to": 8}, {"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 8, "snap_to": 9}]}, {"chain": ["test", "inspect", "inspect", "inspect", "inspect", "write"], "label": "run ./test.sh → inspect test file → inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 10.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 3, "snap_to": 4}]}, {"chain": ["test", "write"], "label": "run ./test.sh → write solution.py", "count": 1, "pct": 10.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "rewrite", "count": 6, "pct": 60.0}, {"label": "fix_bug", "count": 2, "pct": 20.0}, {"label": "implement", "count": 1, "pct": 10.0}, {"label": "debug_failure", "count": 1, "pct": 10.0}], "n_labeled": 10, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 80, "m2": 100, "m6": 60, "m7": 10, "m8_inline": 20, "m3_existing": 30, "m9": 20, "m4": 20}}, {"id": "m21", "source": "churn", "target": "end_limit", "color": "#9C27B0", "count": 4, "out_pct": 19.0, "label": "4", "n_unique_chains": 4, "breakdown": [{"chain": ["test", "test", "inspect"], "label": "run ./test.sh → run ./test.sh → inspect test file", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc373/abc373_f", "snap_from": 10, "snap_to": -1}]}, {"chain": ["inspect", "write_script", "write_script", "write_script"], "label": "inspect test file → write helper script → write helper script → write helper script", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": 4, "snap_to": -1}]}, {"chain": ["inspect"], "label": "inspect test file", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_e", "snap_from": 2, "snap_to": -1}]}, {"chain": [], "label": "(no useful command)", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 7, "snap_to": -1}]}], "label_dist": [{"label": "explore", "count": 2, "pct": 50.0}, {"label": "verify", "count": 2, "pct": 50.0}], "n_labeled": 4, "nlp_rates": {"m1_correctness": 75, "m1_efficiency": 50, "m2": 50, "m3_existing": 75, "m6": 25, "m7": 25, "m9": 25, "m8_lang": 25}}, {"id": "m22", "source": "breakthrough", "target": "broke", "color": "#00BCD4", "count": 1, "out_pct": 1.1, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 0, "snap_to": 1}]}], "label_dist": [{"label": "implement", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m3_existing": 100, "m6": 100, "m7": 100}}, {"id": "m23", "source": "broke", "target": "stuck", "color": "#7B0000", "count": 2, "out_pct": 40.0, "label": "2", "n_unique_chains": 2, "breakdown": [{"chain": ["run_sample", "write"], "label": "run solution.py (sample) → write solution.py", "count": 1, "pct": 50.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 1, "snap_to": 2}]}, {"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 50.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 4, "snap_to": 5}]}], "label_dist": [{"label": "debug_failure", "count": 2, "pct": 100.0}], "n_labeled": 2, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m3_existing": 50, "m9": 50, "m4": 50, "m6": 50}}, {"id": "m24", "source": "stuck", "target": "improved", "color": "#FF9800", "count": 9, "out_pct": 21.4, "label": "9", "n_unique_chains": 3, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 6, "pct": 66.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 11, "snap_to": 12}, {"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 5, "snap_to": 6}, {"problem": "qwen3p6_35b_a3b_fp8/arc184/arc184_d", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc194/arc194_d", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 0, "snap_to": 1}]}, {"chain": ["write_script", "write"], "label": "write helper script → write solution.py", "count": 2, "pct": 22.2, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc385/abc385_e", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 1, "snap_to": 2}]}, {"chain": ["inline_script", "write"], "label": "inline_script → write solution.py", "count": 1, "pct": 11.1, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "fix_bug", "count": 6, "pct": 66.7}, {"label": "rewrite", "count": 2, "pct": 22.2}, {"label": "implement", "count": 1, "pct": 11.1}], "n_labeled": 9, "nlp_rates": {"m1_correctness": 67, "m2": 89, "m3_existing": 11, "m8_lang": 22, "m3_sample": 11, "m6": 33, "m3_own": 11, "m8_inline": 11, "m4": 33, "m1_efficiency": 11, "m9": 11}}, {"id": "m25", "source": "improved", "target": "churn", "color": "#2196F3", "count": 4, "out_pct": 12.9, "label": "4", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 4, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": 0, "snap_to": 1}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "rewrite", "count": 4, "pct": 100.0}], "n_labeled": 4, "nlp_rates": {"m1_correctness": 75, "m1_efficiency": 75, "m2": 100, "m4": 50, "m3_existing": 25}}, {"id": "m26", "source": "churn", "target": "stuck", "color": "#9C27B0", "count": 5, "out_pct": 23.8, "label": "5", "n_unique_chains": 2, "breakdown": [{"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 3, "pct": 60.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 4, "snap_to": 5}, {"problem": "qwen3p6_35b_a3b_fp8/abc390/abc390_e", "snap_from": 2, "snap_to": 3}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 4, "snap_to": 5}]}, {"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 40.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 1, "snap_to": 2}, {"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": 1, "snap_to": 2}]}], "label_dist": [{"label": "implement", "count": 2, "pct": 40.0}, {"label": "fix_bug", "count": 2, "pct": 40.0}, {"label": "rewrite", "count": 1, "pct": 20.0}], "n_labeled": 5, "nlp_rates": {"m1_efficiency": 80, "m2": 100, "m1_correctness": 80, "m3_existing": 60, "m9": 20, "m6": 20}}, {"id": "m27", "source": "stuck", "target": "churn", "color": "#FF9800", "count": 4, "out_pct": 9.5, "label": "4", "n_unique_chains": 4, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc388/abc388_f", "snap_from": 2, "snap_to": 3}]}, {"chain": ["inspect", "inspect", "inspect", "write"], "label": "inspect test file → inspect test file → inspect test file → write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc398/abc398_g", "snap_from": 3, "snap_to": 4}]}, {"chain": ["write_script", "write_script", "write"], "label": "write helper script → write helper script → write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc186/arc186_e", "snap_from": 1, "snap_to": 2}]}, {"chain": ["inspect", "write_script", "write"], "label": "inspect test file → write helper script → write solution.py", "count": 1, "pct": 25.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 5, "snap_to": 6}]}], "label_dist": [{"label": "fix_bug", "count": 2, "pct": 50.0}, {"label": "rewrite", "count": 1, "pct": 25.0}, {"label": "implement", "count": 1, "pct": 25.0}], "n_labeled": 4, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 75, "m2": 100, "m3_existing": 75, "m6": 50, "m8_lang": 50}}, {"id": "m28", "source": "regressed", "target": "broke", "color": "#F44336", "count": 1, "out_pct": 9.1, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "optimize_perf", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100}}, {"id": "m29", "source": "broke", "target": "improved", "color": "#7B0000", "count": 3, "out_pct": 60.0, "label": "3", "n_unique_chains": 2, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 66.7, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 4, "snap_to": 5}, {"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 7, "snap_to": 8}]}, {"chain": ["inspect", "write"], "label": "inspect test file → write solution.py", "count": 1, "pct": 33.3, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "fix_bug", "count": 2, "pct": 66.7}, {"label": "execute_plan", "count": 1, "pct": 33.3}], "n_labeled": 3, "nlp_rates": {"m1_correctness": 67, "m2": 67, "m3_sample": 67, "m1_efficiency": 33, "m3_existing": 33}}, {"id": "m30", "source": "stuck", "target": "broke", "color": "#FF9800", "count": 1, "out_pct": 2.4, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc389/abc389_g", "snap_from": 6, "snap_to": 7}]}], "label_dist": [{"label": "implement", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_efficiency": 100, "m2": 100, "m3_sample": 100}}, {"id": "m31", "source": "churn", "target": "breakthrough", "color": "#9C27B0", "count": 1, "out_pct": 4.8, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["inline_script", "write"], "label": "inline_script → write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc391/abc391_e", "snap_from": 4, "snap_to": 5}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m4": 100, "m6": 100, "m8_inline": 100}}, {"id": "m32", "source": "stay", "target": "end_limit", "color": "#4CAF50", "count": 1, "out_pct": 7.7, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["inspect", "inspect", "inspect", "test", "run_sample", "inline_script", "run_sample", "test", "run_sample", "run_sample", "inline_script", "inline_script"], "label": "inspect test file → inspect test file → inspect test file → run ./test.sh → run solution.py (sample) → inline_script → run solution.py (sample) → run ./test.sh → run solution.py (sample) → run solution.py (sample) → inline_script → inline_script", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc392/abc392_b", "snap_from": 3, "snap_to": -1}]}], "label_dist": [{"label": "debug_failure", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m3_existing": 100, "m6": 100, "m8_inline": 100, "m9": 100}}, {"id": "m33", "source": "stuck", "target": "regressed", "color": "#FF9800", "count": 1, "out_pct": 2.4, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["run_sample", "inspect", "write"], "label": "run solution.py (sample) → inspect test file → write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 1, "snap_to": 2}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m3_existing": 100, "m4": 100, "m6": 100, "m9": 100}}, {"id": "m34", "source": "improved", "target": "broke", "color": "#2196F3", "count": 2, "out_pct": 6.5, "label": "2", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 2, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/abc400/abc400_d", "snap_from": 3, "snap_to": 4}, {"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "implement", "count": 1, "pct": 50.0}, {"label": "explore", "count": 1, "pct": 50.0}], "n_labeled": 2, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m6": 50}}, {"id": "m35", "source": "improved", "target": "improved", "color": "#2196F3", "count": 1, "out_pct": 3.2, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_a", "snap_from": 1, "snap_to": 2}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m2": 100}}, {"id": "m36", "source": "churn", "target": "improved", "color": "#9C27B0", "count": 1, "out_pct": 4.8, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["run_sample", "write"], "label": "run solution.py (sample) → write solution.py", "count": 1, "pct": 100.0, "examples": [{"problem": "qwen3p6_35b_a3b_fp8/arc196/arc196_d", "snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "fix_bug", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m3_existing": 100, "m6": 100}}], "prob_rows": [{"src": "start", "total": 97, "outs": [{"tgt": "breakthrough", "count": 72, "pct": 74.2}, {"tgt": "improved", "count": 14, "pct": 14.4}, {"tgt": "stuck", "count": 11, "pct": 11.3}]}, {"src": "improved", "total": 31, "outs": [{"tgt": "stuck", "count": 7, "pct": 22.6}, {"tgt": "regressed", "count": 6, "pct": 19.4}, {"tgt": "end_limit", "count": 6, "pct": 19.4}, {"tgt": "breakthrough", "count": 5, "pct": 16.1}, {"tgt": "churn", "count": 4, "pct": 12.9}, {"tgt": "broke", "count": 2, "pct": 6.5}, {"tgt": "improved", "count": 1, "pct": 3.2}]}, {"src": "churn", "total": 21, "outs": [{"tgt": "churn", "count": 10, "pct": 47.6}, {"tgt": "stuck", "count": 5, "pct": 23.8}, {"tgt": "end_limit", "count": 4, "pct": 19.0}, {"tgt": "breakthrough", "count": 1, "pct": 4.8}, {"tgt": "improved", "count": 1, "pct": 4.8}]}, {"src": "stuck", "total": 42, "outs": [{"tgt": "stuck", "count": 16, "pct": 38.1}, {"tgt": "improved", "count": 9, "pct": 21.4}, {"tgt": "breakthrough", "count": 6, "pct": 14.3}, {"tgt": "end_limit", "count": 5, "pct": 11.9}, {"tgt": "churn", "count": 4, "pct": 9.5}, {"tgt": "broke", "count": 1, "pct": 2.4}, {"tgt": "regressed", "count": 1, "pct": 2.4}]}, {"src": "breakthrough", "total": 87, "outs": [{"tgt": "end_submit", "count": 74, "pct": 85.1}, {"tgt": "stay", "count": 9, "pct": 10.3}, {"tgt": "regressed", "count": 3, "pct": 3.4}, {"tgt": "broke", "count": 1, "pct": 1.1}]}, {"src": "stay", "total": 13, "outs": [{"tgt": "end_submit", "count": 7, "pct": 53.8}, {"tgt": "stay", "count": 4, "pct": 30.8}, {"tgt": "regressed", "count": 1, "pct": 7.7}, {"tgt": "end_limit", "count": 1, "pct": 7.7}]}, {"src": "regressed", "total": 11, "outs": [{"tgt": "breakthrough", "count": 3, "pct": 27.3}, {"tgt": "improved", "count": 3, "pct": 27.3}, {"tgt": "churn", "count": 3, "pct": 27.3}, {"tgt": "stuck", "count": 1, "pct": 9.1}, {"tgt": "broke", "count": 1, "pct": 9.1}]}, {"src": "broke", "total": 5, "outs": [{"tgt": "improved", "count": 3, "pct": 60.0}, {"tgt": "stuck", "count": 2, "pct": 40.0}]}], "label_rows": [{"label": "cosmetic_refactor", "total": 3, "edges": [{"src": "improved", "tgt": "stuck", "count": 2, "pct": 66.7}, {"src": "breakthrough", "tgt": "stay", "count": 1, "pct": 33.3}]}, {"label": "debug_failure", "total": 13, "edges": [{"src": "stuck", "tgt": "stuck", "count": 4, "pct": 30.8}, {"src": "improved", "tgt": "end_limit", "count": 3, "pct": 23.1}, {"src": "broke", "tgt": "stuck", "count": 2, "pct": 15.4}, {"src": "stuck", "tgt": "end_limit", "count": 1, "pct": 7.7}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 7.7}, {"src": "churn", "tgt": "churn", "count": 1, "pct": 7.7}, {"src": "stay", "tgt": "end_limit", "count": 1, "pct": 7.7}]}, {"label": "execute_plan", "total": 1, "edges": [{"src": "broke", "tgt": "improved", "count": 1, "pct": 100.0}]}, {"label": "explore", "total": 12, "edges": [{"src": "stuck", "tgt": "stuck", "count": 3, "pct": 25.0}, {"src": "start", "tgt": "stuck", "count": 2, "pct": 16.7}, {"src": "improved", "tgt": "end_limit", "count": 2, "pct": 16.7}, {"src": "churn", "tgt": "end_limit", "count": 2, "pct": 16.7}, {"src": "stuck", "tgt": "end_limit", "count": 1, "pct": 8.3}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 8.3}, {"src": "improved", "tgt": "broke", "count": 1, "pct": 8.3}]}, {"label": "fix_bug", "total": 44, "edges": [{"src": "stuck", "tgt": "stuck", "count": 6, "pct": 13.6}, {"src": "stuck", "tgt": "improved", "count": 6, "pct": 13.6}, {"src": "improved", "tgt": "breakthrough", "count": 5, "pct": 11.4}, {"src": "stuck", "tgt": "breakthrough", "count": 4, "pct": 9.1}, {"src": "stay", "tgt": "stay", "count": 2, "pct": 4.5}, {"src": "breakthrough", "tgt": "stay", "count": 2, "pct": 4.5}, {"src": "regressed", "tgt": "improved", "count": 2, "pct": 4.5}, {"src": "churn", "tgt": "churn", "count": 2, "pct": 4.5}, {"src": "churn", "tgt": "stuck", "count": 2, "pct": 4.5}, {"src": "stuck", "tgt": "churn", "count": 2, "pct": 4.5}, {"src": "broke", "tgt": "improved", "count": 2, "pct": 4.5}, {"src": "regressed", "tgt": "breakthrough", "count": 1, "pct": 2.3}, {"src": "breakthrough", "tgt": "regressed", "count": 1, "pct": 2.3}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 2.3}, {"src": "improved", "tgt": "regressed", "count": 1, "pct": 2.3}, {"src": "regressed", "tgt": "churn", "count": 1, "pct": 2.3}, {"src": "churn", "tgt": "breakthrough", "count": 1, "pct": 2.3}, {"src": "stuck", "tgt": "regressed", "count": 1, "pct": 2.3}, {"src": "improved", "tgt": "improved", "count": 1, "pct": 2.3}, {"src": "churn", "tgt": "improved", "count": 1, "pct": 2.3}]}, {"label": "implement", "total": 108, "edges": [{"src": "start", "tgt": "breakthrough", "count": 72, "pct": 66.7}, {"src": "start", "tgt": "improved", "count": 14, "pct": 13.0}, {"src": "start", "tgt": "stuck", "count": 9, "pct": 8.3}, {"src": "breakthrough", "tgt": "stay", "count": 2, "pct": 1.9}, {"src": "churn", "tgt": "stuck", "count": 2, "pct": 1.9}, {"src": "stuck", "tgt": "stuck", "count": 1, "pct": 0.9}, {"src": "regressed", "tgt": "breakthrough", "count": 1, "pct": 0.9}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 0.9}, {"src": "churn", "tgt": "churn", "count": 1, "pct": 0.9}, {"src": "breakthrough", "tgt": "broke", "count": 1, "pct": 0.9}, {"src": "stuck", "tgt": "improved", "count": 1, "pct": 0.9}, {"src": "stuck", "tgt": "churn", "count": 1, "pct": 0.9}, {"src": "stuck", "tgt": "broke", "count": 1, "pct": 0.9}, {"src": "improved", "tgt": "broke", "count": 1, "pct": 0.9}]}, {"label": "optimize_perf", "total": 12, "edges": [{"src": "improved", "tgt": "regressed", "count": 3, "pct": 25.0}, {"src": "stay", "tgt": "stay", "count": 2, "pct": 16.7}, {"src": "stuck", "tgt": "stuck", "count": 1, "pct": 8.3}, {"src": "stay", "tgt": "regressed", "count": 1, "pct": 8.3}, {"src": "regressed", "tgt": "breakthrough", "count": 1, "pct": 8.3}, {"src": "breakthrough", "tgt": "stay", "count": 1, "pct": 8.3}, {"src": "breakthrough", "tgt": "regressed", "count": 1, "pct": 8.3}, {"src": "regressed", "tgt": "churn", "count": 1, "pct": 8.3}, {"src": "regressed", "tgt": "broke", "count": 1, "pct": 8.3}]}, {"label": "rewrite", "total": 25, "edges": [{"src": "churn", "tgt": "churn", "count": 6, "pct": 24.0}, {"src": "improved", "tgt": "churn", "count": 4, "pct": 16.0}, {"src": "stuck", "tgt": "breakthrough", "count": 2, "pct": 8.0}, {"src": "improved", "tgt": "regressed", "count": 2, "pct": 8.0}, {"src": "improved", "tgt": "stuck", "count": 2, "pct": 8.0}, {"src": "stuck", "tgt": "improved", "count": 2, "pct": 8.0}, {"src": "stuck", "tgt": "stuck", "count": 1, "pct": 4.0}, {"src": "breakthrough", "tgt": "stay", "count": 1, "pct": 4.0}, {"src": "breakthrough", "tgt": "regressed", "count": 1, "pct": 4.0}, {"src": "regressed", "tgt": "improved", "count": 1, "pct": 4.0}, {"src": "regressed", "tgt": "churn", "count": 1, "pct": 4.0}, {"src": "churn", "tgt": "stuck", "count": 1, "pct": 4.0}, {"src": "stuck", "tgt": "churn", "count": 1, "pct": 4.0}]}, {"label": "verify", "total": 89, "edges": [{"src": "breakthrough", "tgt": "end_submit", "count": 74, "pct": 83.1}, {"src": "stay", "tgt": "end_submit", "count": 7, "pct": 7.9}, {"src": "stuck", "tgt": "end_limit", "count": 3, "pct": 3.4}, {"src": "breakthrough", "tgt": "stay", "count": 2, "pct": 2.2}, {"src": "churn", "tgt": "end_limit", "count": 2, "pct": 2.2}, {"src": "improved", "tgt": "end_limit", "count": 1, "pct": 1.1}]}], "n_problems": 97, "max_count": 74, "lang": "python", "model_scope": "qwen"};

	function esc(s) {
	return String(s).replace(/&/g,'&').replace(/</g,'<')
	.replace(/>/g,'>').replace(/"/g,'"');
	}
	function snapLabel(idx) {
	if (idx < 0) return idx === -1 ? 'end' : 'start';
	return 'snap_' + String(idx).padStart(2,'0');
	}

	// Action-kind palette (text / background) — must mirror Python's KIND_COLOR.
	const AKC = {
	'write': ['#166534', '#dcfce7'],
	'write_script': ['#7c3aed', '#f5f3ff'],
	'run_sample': ['#0369a1', '#e0f2fe'],
	'run_script': ['#0284c7', '#e0f2fe'],
	'test': ['#b45309', '#fffbeb'],
	'time': ['#ca8a04', '#fefce8'],
	'inspect': ['#475569', '#f1f5f9'],
	'wc': ['#64748b', '#f1f5f9'],
	'diff': ['#64748b', '#f1f5f9'],
	'submit': ['#dc2626', '#fef2f2'],
	};
	// Compact pill labels (chain display).
	const KIND_SHORT = {
	'write': 'cat > solution',
	'write_script': 'cat > helper.py',
	'run_sample': 'python3 solution.py',
	'run_script': 'python3 script.py',
	'test': './test.sh',
	'time': 'time solution.py',
	'inspect': 'cat tests/',
	'wc': 'wc',
	'diff': 'diff',
	'submit': 'echo COMPLETE_TASK',
	};
	// Gap label palette [text, background] — covers both old and new taxonomy labels
	const LABEL_COLORS = {
	// new taxonomy
	'fix_bug': ['#166534', '#dcfce7'],
	'debug_failure': ['#dc2626', '#fef2f2'],
	'implement': ['#1d4ed8', '#eff6ff'],
	'rewrite': ['#7c3aed', '#f5f3ff'],
	'explore': ['#0891b2', '#ecfeff'],
	'execute_plan': ['#0f766e', '#f0fdfa'],
	'revert': ['#6b7280', '#f9fafb'],
	'verify': ['#334155', '#f1f5f9'],
	'edge_case': ['#65a30d', '#f7fee7'],
	'optimize_perf': ['#6d28d9', '#f5f3ff'],
	'cosmetic_refactor': ['#475569', '#f1f5f9'],
	'infra_confusion': ['#ca8a04', '#fefce8'],
	// old taxonomy (v1)
	'initial_impl': ['#166534', '#dcfce7'],
	'run_tests': ['#0369a1', '#e0f2fe'],
	'fix_specific_failure':['#ea580c', '#fff7ed'],
	'rethink_algorithm': ['#d97706', '#fffbeb'],
	'complete_partial': ['#0891b2', '#ecfeff'],
	'fix_crash': ['#b91c1c', '#fef2f2'],
	'read_tests': ['#0284c7', '#f0f9ff'],
	'attempt': ['#1d4ed8', '#eff6ff'],
	};
	function renderLabelDist(labelDist, nLabeled) {
	if (!labelDist \|\| !labelDist.length) return '';
	let h = `<div class="det-sub">Gap label distribution (${nLabeled} labeled)</div>`;
	labelDist.forEach(d => {
	const [fg, bg] = LABEL_COLORS[d.label] \|\| ['#374151', '#f9fafb'];
	h += `<div class="lbl-row">`;
	h += `<div class="lbl-head">`;
	h += `<span class="lbl-pill" style="color:${fg};background:${bg}">${esc(d.label)}</span>`;
	h += `<span class="lbl-num">${d.count} · ${d.pct}%</span></div>`;
	h += `<div class="lbl-bar"><div class="lbl-fill" style="width:${d.pct}%;background:${fg}"></div></div>`;
	h += `</div>`;
	});
	return h;
	}

	function renderGapDist(dist, total, title) {
	if (!dist \|\| !Object.keys(dist).length) return '';
	const entries = Object.entries(dist).sort((a, b) => b[1] - a[1]);
	let h = `<div class="det-sub">${esc(title)} (${total} labeled)</div>`;
	entries.forEach(([lbl, pct]) => {
	const [fg, bg] = LABEL_COLORS[lbl] \|\| ['#374151', '#f9fafb'];
	h += `<div class="lbl-row">`;
	h += `<div class="lbl-head">`;
	h += `<span class="lbl-pill" style="color:${fg};background:${bg}">${esc(lbl)}</span>`;
	h += `<span class="lbl-num">${pct}%</span></div>`;
	h += `<div class="lbl-bar"><div class="lbl-fill" style="width:${pct}%;background:${fg}"></div></div>`;
	h += `</div>`;
	});
	return h;
	}

	const NLP_LABELS = {
	'm1_correctness': 'M1 correctness',
	'm1_efficiency': 'M1 efficiency',
	'm1_clarity': 'M1 clarity',
	'm2': 'M2 second-guess',
	'm3_existing': 'M3 existing tests',
	'm3_own': 'M3 own tests',
	'm4': 'M4 # comment',
	'm6': 'M6 code fence',
	'm7': 'M7 edge case',
	'm8_lang': 'M8a extra lang',
	'm8_python': 'M8b extra .py',
	'm9': 'M9 error turn',
	};
	const NLP_KEY_ORDER = ['m1_correctness','m1_efficiency','m1_clarity','m2',
	'm3_existing','m3_own','m4','m6','m7','m8_lang','m8_python','m9'];

	function renderNlpDist(rates, total, title) {
	if (!rates \|\| !Object.keys(rates).length) return '';
	const entries = NLP_KEY_ORDER
	.filter(k => (rates[k] \|\| 0) > 0)
	.map(k => [k, rates[k]]);
	if (!entries.length) return '';
	let h = `<div class="det-sub">${esc(title)} (${total} edges)</div>`;
	entries.forEach(([k, pct]) => {
	const lbl = NLP_LABELS[k] \|\| k;
	h += `<div class="nlp-row">`;
	h += `<span class="nlp-lbl">${esc(lbl)}</span>`;
	h += `<span class="nlp-bar"><span class="nlp-fill" style="width:${pct}%"></span></span>`;
	h += `<span class="nlp-num">${pct}%</span></div>`;
	});
	return h;
	}

	function renderNlpRates(rates) {
	if (!rates \|\| !Object.keys(rates).length) return '';
	const chips = NLP_KEY_ORDER
	.filter(k => (rates[k] \|\| 0) > 0)
	.map(k => `<span class="nlp-chip">${esc(NLP_LABELS[k] \|\| k)}: ${rates[k]}%</span>`)
	.join('');
	if (!chips) return '';
	return `<div class="det-sub">NLP signals (% of traversals)</div><div style="margin-bottom:6px">${chips}</div>`;
	}

	function renderChain(chain) {
	if (!chain \|\| !chain.length)
	return '<span class="kind-pill" style="color:#94a3b8;background:#f1f5f9">(no useful command)</span>';
	return chain.map((k, i) => {
	const [fg, bg] = AKC[k] \|\| ['#374151', '#f9fafb'];
	const lbl = KIND_SHORT[k] \|\| k;
	const arrow = i > 0 ? '<span class="kind-arrow">→</span>' : '';
	return arrow + `<span class="kind-pill" style="color:${fg};background:${bg}">${esc(lbl)}</span>`;
	}).join('');
	}

	function showEdgeDetail(panel, ed) {
	const sc = (M.nodes.find(n => n.id === ed.source) \|\| {}).color \|\| ed.color;
	const tc = (M.nodes.find(n => n.id === ed.target) \|\| {}).color \|\| '#9e9e9e';
	let h = `<div class="det-title">`;
	h += `<span class="state-chip" style="background:${sc}">${esc(ed.source)}</span>`;
	h += `<span style="color:#94a3b8;font-weight:400">→</span>`;
	h += `<span class="state-chip" style="background:${tc}">${esc(ed.target)}</span></div>`;
	h += `<div class="det-row"><span class="det-lbl">Count</span><span class="det-val">${ed.count}</span></div>`;
	h += `<div class="det-row"><span class="det-lbl">P(${esc(ed.target)} \| ${esc(ed.source)})</span>`;
	h += `<span class="det-val">${ed.out_pct}%</span></div>`;

	h += `<div class="det-sub">Command-chain breakdown (${ed.n_unique_chains} distinct chain${ed.n_unique_chains === 1 ? '' : 's'})</div>`;
	(ed.breakdown \|\| []).forEach(b => {
	h += `<div class="bd-row">`;
	h += `<div class="bd-head"><span class="bd-lbl">${renderChain(b.chain)}</span>`;
	h += `<span class="bd-num">${b.count} · ${b.pct}%</span></div>`;
	h += `<div class="bd-bar"><div class="bd-fill" style="width:${b.pct}%;background:#94a3b8"></div></div>`;
	(b.examples \|\| []).forEach(ex => {
	const fr = ex.snap_from < 0 ? 'start' : snapLabel(ex.snap_from);
	const to = ex.snap_to < 0
	? (ed.target === 'end_limit' ? 'limit' : 'submit')
	: snapLabel(ex.snap_to);
	h += `<div class="bd-ex">${esc(ex.problem)} ${fr}→${to}</div>`;
	});
	h += `</div>`;
	});
	h += renderLabelDist(ed.label_dist, ed.n_labeled);
	h += renderNlpRates(ed.nlp_rates);
	panel.innerHTML = h;
	}

	function showNodeDetail(panel, n) {
	let h = `<div class="det-title"><span class="state-chip" style="background:${n.color}">${n.state_type}</span></div>`;
	h += `<div class="det-def">${esc(n.definition)}</div>`;
	h += `<div class="det-row"><span class="det-lbl">Visits</span><span class="det-val">${n.visits}</span></div>`;
	h += `<div class="det-row"><span class="det-lbl">Outgoing</span><span class="det-val">${n.out_total}</span></div>`;

	const outs = M.edges.filter(e => e.source === n.id)
	.sort((a,b) => b.count - a.count);
	if (outs.length) {
	h += `<div class="det-sub">Outgoing distribution (sums to 100%)</div>`;
	outs.forEach(e => {
	const tcol = (M.nodes.find(nd => nd.id === e.target) \|\| {}).color \|\| e.color;
	h += `<div class="out-row">`;
	h += `<span class="out-tgt" style="color:${tcol}">${esc(e.target)}</span>`;
	h += `<span class="out-bar"><span class="out-fill" style="width:${e.out_pct}%;background:${tcol}"></span></span>`;
	h += `<span class="out-num">${e.out_pct}% (${e.count})</span></div>`;
	});
	} else {
	h += `<div class="det-def">Terminal state — no outgoing transitions.</div>`;
	}

	const ins = M.edges.filter(e => e.target === n.id)
	.sort((a,b) => b.count - a.count);
	if (ins.length) {
	const inTotal = ins.reduce((s, e) => s + e.count, 0);
	h += `<div class="det-sub">Incoming distribution (sums to 100%)</div>`;
	ins.forEach(e => {
	const scol = (M.nodes.find(nd => nd.id === e.source) \|\| {}).color \|\| e.color;
	const pct = inTotal > 0 ? Math.round(1000 * e.count / inTotal) / 10 : 0;
	h += `<div class="out-row">`;
	h += `<span class="out-tgt" style="color:${scol}">${esc(e.source)}</span>`;
	h += `<span class="out-bar"><span class="out-fill" style="width:${pct}%;background:${scol}"></span></span>`;
	h += `<span class="out-num">${pct}% (${e.count})</span></div>`;
	});
	}
	h += renderGapDist(n.gap_out, n.gap_out_total, 'Outgoing gap labels');
	h += renderGapDist(n.gap_in, n.gap_in_total, 'Incoming gap labels');
	h += renderNlpDist(n.nlp_out, n.nlp_out_total, 'Outgoing NLP signals');
	h += renderNlpDist(n.nlp_in, n.nlp_in_total, 'Incoming NLP signals');
	panel.innerHTML = h;
	}

	function makeBgImg(count, w, h, fs) {
	if (!count) return '';
	const svg = '<svg xmlns="http://www.w3.org/2000/svg" width="' + w + '" height="' + h + '"><text x="' + (w/2) + '" y="' + Math.round(h*0.8) + '" text-anchor="middle" font-family="ui-monospace,monospace" font-size="' + fs + '" fill="white" font-weight="700">' + count + '</text></svg>';
	return 'data:image/svg+xml;charset=utf-8,' + encodeURIComponent(svg);
	}

	const cyNodes = M.nodes.map(n => {
	const sp = n.id === 'start' \|\| n.id === 'end_submit' \|\| n.id === 'end_limit';
	const nw = sp ? 54 : 72, nh = sp ? 54 : 72;
	return {
	data: { id: n.id, label: n.label, color: n.color, n,
	bgImg: makeBgImg(n.visits, nw, nh, 9) },
	position: { x: n.x, y: n.y },
	};
	});

	const cyEdges = M.edges.map(ed => ({
	data: {
	id: ed.id, source: ed.source, target: ed.target,
	label: ed.label, color: ed.color,
	isSelf: ed.source === ed.target ? 'yes' : 'no',
	// width scales with outgoing probability (thicker = more likely)
	// edge thickness scales with ABSOLUTE count (normalised against the
	// graph's max count so the thickest edge fills the visible range).
	width: 1.0 + (ed.count / Math.max(1, M.max_count)) * 9.0,
	ed,
	}
	}));

	const cy = cytoscape({
	container: document.getElementById('cy'),
	elements: { nodes: cyNodes, edges: cyEdges },
	layout: { name: 'preset' },
	style: [
	{
	selector: 'node',
	style: {
	'background-color': 'data(color)', 'label': 'data(label)', 'color': 'white',
	'font-size': '11px', 'font-weight': '700',
	'text-valign': 'center', 'text-halign': 'center',
	'width': 72, 'height': 72, 'border-width': 3, 'border-color': 'white',
	'background-image': 'data(bgImg)',
	'background-fit': 'contain',
	}
	},
	{
	selector: 'node[id = "start"], node[id = "end_submit"], node[id = "end_limit"]',
	style: { 'shape': 'round-rectangle', 'width': 54, 'height': 54,
	'background-color': '#94a3b8', 'border-color': '#64748b' }
	},
	{
	selector: 'node[id = "start"]',
	style: { 'font-size': '16px' }
	},
	{
	selector: 'node:selected',
	style: { 'border-color': '#0f172a', 'border-width': 4 }
	},
	{
	selector: 'edge',
	style: {
	'width': 'data(width)',
	'line-color': 'data(color)',
	'target-arrow-color': 'data(color)',
	'target-arrow-shape': 'triangle',
	'arrow-scale': 1.0,
	'curve-style': 'bezier',
	'target-label': 'data(label)',
	'target-text-offset': 24,
	'font-size': '9px',
	'font-weight': '700',
	'font-family': 'ui-monospace, monospace',
	'color': '#1e293b',
	'text-background-opacity': 0.92,
	'text-background-color': 'white',
	'text-background-padding': '2px',
	'opacity': 0.78,
	}
	},
	{
	selector: 'edge[isSelf = "yes"]',
	style: { 'curve-style': 'loop', 'loop-direction': '0deg',
	'loop-sweep': '70deg' }
	},
	{
	selector: 'edge:selected',
	style: { 'opacity': 1, 'font-size': '11px', 'z-index': 999, 'line-color': '#0f172a',
	'target-arrow-color': '#0f172a' }
	},
	],
	userZoomingEnabled: true,
	userPanningEnabled: true,
	boxSelectionEnabled: false,
	});
	cy.fit(cy.elements(), 40);

	const panel = document.getElementById('detail');
	cy.on('tap', 'node', evt => showNodeDetail(panel, evt.target.data('n')));
	cy.on('tap', 'edge', evt => showEdgeDetail(panel, evt.target.data('ed')));
	cy.on('tap', evt => {
	if (evt.target === cy)
	panel.innerHTML = '<div class="detail-placeholder">Click a node or edge for details</div>';
	});
	cy.on('mouseover', 'edge', evt => evt.target.style({ opacity: 1 }));
	cy.on('mouseout', 'edge', evt => { if (!evt.target.selected()) evt.target.style({ opacity: 0.78 }); });
	</script>
	</body>
	</html>