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	<!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>
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	display: flex; align-items: center; gap: 6px; flex-wrap: wrap; }
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	.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; }
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	.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; }
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	.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; }
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	font-size: 0.7rem; color: #475569; }
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	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 · gemma · 100 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">100</td><td class="tr-sum">100%</td><td style="text-align:left">breakthrough <b>73.0%</b> <span style="color:#94a3b8">(73)</span>   stuck <b>17.0%</b> <span style="color:#94a3b8">(17)</span>   improved <b>10.0%</b> <span style="color:#94a3b8">(10)</span></td></tr><tr><td class="tr-name">improved</td><td class="tr-total">39</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>38.5%</b> <span style="color:#94a3b8">(15)</span>   regressed <b>17.9%</b> <span style="color:#94a3b8">(7)</span>   breakthrough <b>12.8%</b> <span style="color:#94a3b8">(5)</span>   improved <b>10.3%</b> <span style="color:#94a3b8">(4)</span>   end_limit <b>10.3%</b> <span style="color:#94a3b8">(4)</span>   broke <b>5.1%</b> <span style="color:#94a3b8">(2)</span>   churn <b>2.6%</b> <span style="color:#94a3b8">(1)</span>   end_submit <b>2.6%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">churn</td><td class="tr-total">4</td><td class="tr-sum">100%</td><td style="text-align:left">broke <b>50.0%</b> <span style="color:#94a3b8">(2)</span>   breakthrough <b>25.0%</b> <span style="color:#94a3b8">(1)</span>   churn <b>25.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">stuck</td><td class="tr-total">99</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>52.5%</b> <span style="color:#94a3b8">(52)</span>   improved <b>17.2%</b> <span style="color:#94a3b8">(17)</span>   breakthrough <b>12.1%</b> <span style="color:#94a3b8">(12)</span>   end_submit <b>7.1%</b> <span style="color:#94a3b8">(7)</span>   broke <b>5.1%</b> <span style="color:#94a3b8">(5)</span>   end_limit <b>4.0%</b> <span style="color:#94a3b8">(4)</span>   regressed <b>2.0%</b> <span style="color:#94a3b8">(2)</span></td></tr><tr><td class="tr-name">breakthrough</td><td class="tr-total">98</td><td class="tr-sum">100%</td><td style="text-align:left">stay <b>55.1%</b> <span style="color:#94a3b8">(54)</span>   end_submit <b>40.8%</b> <span style="color:#94a3b8">(40)</span>   regressed <b>3.1%</b> <span style="color:#94a3b8">(3)</span>   broke <b>1.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">stay</td><td class="tr-total">279</td><td class="tr-sum">100%</td><td style="text-align:left">stay <b>80.6%</b> <span style="color:#94a3b8">(225)</span>   end_submit <b>11.8%</b> <span style="color:#94a3b8">(33)</span>   end_limit <b>3.6%</b> <span style="color:#94a3b8">(10)</span>   broke <b>3.2%</b> <span style="color:#94a3b8">(9)</span>   regressed <b>0.7%</b> <span style="color:#94a3b8">(2)</span></td></tr><tr><td class="tr-name">regressed</td><td class="tr-total">15</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>40.0%</b> <span style="color:#94a3b8">(6)</span>   improved <b>26.7%</b> <span style="color:#94a3b8">(4)</span>   churn <b>13.3%</b> <span style="color:#94a3b8">(2)</span>   breakthrough <b>6.7%</b> <span style="color:#94a3b8">(1)</span>   regressed <b>6.7%</b> <span style="color:#94a3b8">(1)</span>   end_limit <b>6.7%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">broke</td><td class="tr-total">19</td><td class="tr-sum">100%</td><td style="text-align:left">stuck <b>47.4%</b> <span style="color:#94a3b8">(9)</span>   breakthrough <b>31.6%</b> <span style="color:#94a3b8">(6)</span>   improved <b>21.1%</b> <span style="color:#94a3b8">(4)</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">105</td><td style="text-align:left">stay→stay <b>75.2%</b> <span style="color:#94a3b8">(79)</span>   breakthrough→stay <b>12.4%</b> <span style="color:#94a3b8">(13)</span>   improved→stuck <b>4.8%</b> <span style="color:#94a3b8">(5)</span>   stuck→stuck <b>4.8%</b> <span style="color:#94a3b8">(5)</span>   regressed→stuck <b>1.0%</b> <span style="color:#94a3b8">(1)</span>   broke→breakthrough <b>1.0%</b> <span style="color:#94a3b8">(1)</span>   stay→regressed <b>1.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">debug_failure</td><td class="tr-total">17</td><td style="text-align:left">stuck→stuck <b>29.4%</b> <span style="color:#94a3b8">(5)</span>   stay→stay <b>23.5%</b> <span style="color:#94a3b8">(4)</span>   broke→stuck <b>11.8%</b> <span style="color:#94a3b8">(2)</span>   stuck→broke <b>5.9%</b> <span style="color:#94a3b8">(1)</span>   improved→stuck <b>5.9%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>5.9%</b> <span style="color:#94a3b8">(1)</span>   stay→end_limit <b>5.9%</b> <span style="color:#94a3b8">(1)</span>   improved→end_limit <b>5.9%</b> <span style="color:#94a3b8">(1)</span>   churn→churn <b>5.9%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">edge_case</td><td class="tr-total">9</td><td style="text-align:left">stay→stay <b>66.7%</b> <span style="color:#94a3b8">(6)</span>   breakthrough→stay <b>22.2%</b> <span style="color:#94a3b8">(2)</span>   regressed→churn <b>11.1%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">execute_plan</td><td class="tr-total">12</td><td style="text-align:left">stuck→improved <b>41.7%</b> <span style="color:#94a3b8">(5)</span>   stuck→breakthrough <b>25.0%</b> <span style="color:#94a3b8">(3)</span>   stay→stay <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→stay <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   broke→stuck <b>8.3%</b> <span style="color:#94a3b8">(1)</span>   broke→breakthrough <b>8.3%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">explore</td><td class="tr-total">51</td><td style="text-align:left">stuck→stuck <b>25.5%</b> <span style="color:#94a3b8">(13)</span>   start→stuck <b>25.5%</b> <span style="color:#94a3b8">(13)</span>   stay→broke <b>13.7%</b> <span style="color:#94a3b8">(7)</span>   broke→stuck <b>9.8%</b> <span style="color:#94a3b8">(5)</span>   stay→stay <b>7.8%</b> <span style="color:#94a3b8">(4)</span>   stuck→broke <b>5.9%</b> <span style="color:#94a3b8">(3)</span>   improved→broke <b>3.9%</b> <span style="color:#94a3b8">(2)</span>   start→improved <b>2.0%</b> <span style="color:#94a3b8">(1)</span>   improved→stuck <b>2.0%</b> <span style="color:#94a3b8">(1)</span>   stuck→improved <b>2.0%</b> <span style="color:#94a3b8">(1)</span>   breakthrough→broke <b>2.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">fix_bug</td><td class="tr-total">55</td><td style="text-align:left">stay→stay <b>36.4%</b> <span style="color:#94a3b8">(20)</span>   breakthrough→stay <b>10.9%</b> <span style="color:#94a3b8">(6)</span>   stuck→stuck <b>7.3%</b> <span style="color:#94a3b8">(4)</span>   stuck→breakthrough <b>7.3%</b> <span style="color:#94a3b8">(4)</span>   improved→regressed <b>7.3%</b> <span style="color:#94a3b8">(4)</span>   stuck→improved <b>5.5%</b> <span style="color:#94a3b8">(3)</span>   improved→improved <b>5.5%</b> <span style="color:#94a3b8">(3)</span>   improved→stuck <b>3.6%</b> <span style="color:#94a3b8">(2)</span>   improved→breakthrough <b>3.6%</b> <span style="color:#94a3b8">(2)</span>   broke→improved <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   improved→churn <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   broke→breakthrough <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→breakthrough <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→churn <b>1.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→improved <b>1.8%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">implement</td><td class="tr-total">162</td><td style="text-align:left">start→breakthrough <b>45.1%</b> <span style="color:#94a3b8">(73)</span>   stay→stay <b>21.6%</b> <span style="color:#94a3b8">(35)</span>   breakthrough→stay <b>7.4%</b> <span style="color:#94a3b8">(12)</span>   start→improved <b>5.6%</b> <span style="color:#94a3b8">(9)</span>   stuck→stuck <b>3.7%</b> <span style="color:#94a3b8">(6)</span>   stuck→improved <b>3.1%</b> <span style="color:#94a3b8">(5)</span>   improved→stuck <b>2.5%</b> <span style="color:#94a3b8">(4)</span>   start→stuck <b>2.5%</b> <span style="color:#94a3b8">(4)</span>   breakthrough→regressed <b>1.9%</b> <span style="color:#94a3b8">(3)</span>   stuck→breakthrough <b>1.2%</b> <span style="color:#94a3b8">(2)</span>   regressed→improved <b>1.2%</b> <span style="color:#94a3b8">(2)</span>   stuck→regressed <b>1.2%</b> <span style="color:#94a3b8">(2)</span>   broke→improved <b>0.6%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>0.6%</b> <span style="color:#94a3b8">(1)</span>   broke→breakthrough <b>0.6%</b> <span style="color:#94a3b8">(1)</span>   improved→breakthrough <b>0.6%</b> <span style="color:#94a3b8">(1)</span>   improved→regressed <b>0.6%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">infra_confusion</td><td class="tr-total">5</td><td style="text-align:left">stay→stay <b>60.0%</b> <span style="color:#94a3b8">(3)</span>   stay→end_submit <b>20.0%</b> <span style="color:#94a3b8">(1)</span>   stay→broke <b>20.0%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">optimize_perf</td><td class="tr-total">66</td><td style="text-align:left">stay→stay <b>59.1%</b> <span style="color:#94a3b8">(39)</span>   breakthrough→stay <b>25.8%</b> <span style="color:#94a3b8">(17)</span>   stuck→breakthrough <b>4.5%</b> <span style="color:#94a3b8">(3)</span>   improved→stuck <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   stuck→stuck <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   broke→stuck <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   improved→improved <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   improved→breakthrough <b>1.5%</b> <span style="color:#94a3b8">(1)</span>   stay→regressed <b>1.5%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">revert</td><td class="tr-total">24</td><td style="text-align:left">stay→stay <b>58.3%</b> <span style="color:#94a3b8">(14)</span>   stuck→stuck <b>33.3%</b> <span style="color:#94a3b8">(8)</span>   improved→stuck <b>4.2%</b> <span style="color:#94a3b8">(1)</span>   churn→breakthrough <b>4.2%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">rewrite</td><td class="tr-total">26</td><td style="text-align:left">stuck→stuck <b>26.9%</b> <span style="color:#94a3b8">(7)</span>   stuck→improved <b>11.5%</b> <span style="color:#94a3b8">(3)</span>   breakthrough→stay <b>7.7%</b> <span style="color:#94a3b8">(2)</span>   broke→improved <b>7.7%</b> <span style="color:#94a3b8">(2)</span>   churn→broke <b>7.7%</b> <span style="color:#94a3b8">(2)</span>   broke→breakthrough <b>7.7%</b> <span style="color:#94a3b8">(2)</span>   improved→regressed <b>7.7%</b> <span style="color:#94a3b8">(2)</span>   stuck→broke <b>3.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→stuck <b>3.8%</b> <span style="color:#94a3b8">(1)</span>   stay→broke <b>3.8%</b> <span style="color:#94a3b8">(1)</span>   improved→breakthrough <b>3.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→regressed <b>3.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→improved <b>3.8%</b> <span style="color:#94a3b8">(1)</span></td></tr><tr><td class="tr-name">verify</td><td class="tr-total">121</td><td style="text-align:left">breakthrough→end_submit <b>33.1%</b> <span style="color:#94a3b8">(40)</span>   stay→end_submit <b>25.6%</b> <span style="color:#94a3b8">(31)</span>   stay→stay <b>16.5%</b> <span style="color:#94a3b8">(20)</span>   stay→end_limit <b>8.3%</b> <span style="color:#94a3b8">(10)</span>   stuck→end_submit <b>5.0%</b> <span style="color:#94a3b8">(6)</span>   stuck→end_limit <b>4.1%</b> <span style="color:#94a3b8">(5)</span>   stuck→stuck <b>2.5%</b> <span style="color:#94a3b8">(3)</span>   improved→end_limit <b>2.5%</b> <span style="color:#94a3b8">(3)</span>   breakthrough→stay <b>0.8%</b> <span style="color:#94a3b8">(1)</span>   regressed→end_limit <b>0.8%</b> <span style="color:#94a3b8">(1)</span>   improved→end_submit <b>0.8%</b> <span style="color:#94a3b8">(1)</span></td></tr></tbody>
	</table>
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"snap_to": -1}, {"problem": "gemma_4_26b_a4b_it/abc378/abc378_g", "snap_from": 4, "snap_to": -1}, {"problem": "gemma_4_26b_a4b_it/abc398/abc398_g", "snap_from": 11, "snap_to": -1}, {"problem": "gemma_4_26b_a4b_it/arc194/arc194_a", "snap_from": 6, "snap_to": -1}]}], "label_dist": [{"label": "verify", "count": 5, "pct": 100.0}], "n_labeled": 5, "nlp_rates": {}}, {"id": "m25", "source": "improved", "target": "breakthrough", "color": "#2196F3", "count": 5, "out_pct": 12.8, "label": "5", "n_unique_chains": 2, "breakdown": [{"chain": ["write"], "label": "write solution.py", "count": 4, "pct": 80.0, "examples": [{"problem": "gemma_4_26b_a4b_it/abc373/abc373_f", "snap_from": 0, "snap_to": 1}, {"problem": "gemma_4_26b_a4b_it/abc397/abc397_e", "snap_from": 0, "snap_to": 1}, {"problem": "gemma_4_26b_a4b_it/arc194/arc194_b", "snap_from": 4, "snap_to": 5}, {"problem": "gemma_4_26b_a4b_it/arc194/arc194_e", "snap_from": 0, "snap_to": 1}]}, {"chain": ["run_sample", "write_script", "write"], "label": 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"snap_to": 6}, {"problem": "gemma_4_26b_a4b_it/arc184/arc184_d", "snap_from": 10, "snap_to": 11}, {"problem": "gemma_4_26b_a4b_it/arc186/arc186_e", "snap_from": 1, "snap_to": 2}, {"problem": "gemma_4_26b_a4b_it/arc194/arc194_b", "snap_from": 3, "snap_to": 4}]}], "label_dist": [{"label": "implement", "count": 2, "pct": 50.0}, {"label": "fix_bug", "count": 1, "pct": 25.0}, {"label": "rewrite", "count": 1, "pct": 25.0}], "n_labeled": 4, "nlp_rates": {"m1_correctness": 100, "m2": 100, "m3_sample": 75, "m3_own": 50, "m9": 50, "m3_existing": 25}}, {"id": "m33", "source": "improved", "target": "end_limit", "color": "#2196F3", "count": 4, "out_pct": 10.3, "label": "4", "n_unique_chains": 2, "breakdown": [{"chain": [], "label": "(no useful command)", "count": 3, "pct": 75.0, "examples": [{"problem": "gemma_4_26b_a4b_it/arc184/arc184_d", "snap_from": 11, "snap_to": -1}, {"problem": "gemma_4_26b_a4b_it/arc186/arc186_e", "snap_from": 10, "snap_to": -1}, {"problem": 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"snap_from": 2, "snap_to": 3}]}], "label_dist": [{"label": "implement", "count": 2, "pct": 100.0}], "n_labeled": 2, "nlp_rates": {"m1_correctness": 100, "m1_efficiency": 100, "m2": 100, "m3_sample": 50, "m4": 50, "m6": 50, "m3_existing": 50, "m9": 50}}, {"id": "m37", "source": "regressed", "target": "end_limit", "color": "#F44336", "count": 1, "out_pct": 6.7, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": [], "label": "(no useful command)", "count": 1, "pct": 100.0, "examples": [{"problem": "gemma_4_26b_a4b_it/arc191/arc191_d", "snap_from": 10, "snap_to": -1}]}], "label_dist": [{"label": "verify", "count": 1, "pct": 100.0}], "n_labeled": 1, "nlp_rates": {}}, {"id": "m38", "source": "improved", "target": "end_submit", "color": "#2196F3", "count": 1, "out_pct": 2.6, "label": "1", "n_unique_chains": 1, "breakdown": [{"chain": ["submit"], "label": "submit", "count": 1, "pct": 100.0, "examples": [{"problem": "gemma_4_26b_a4b_it/arc193/arc193_a", "snap_from": 19, "snap_to": 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"broke", "tgt": "stuck", "count": 2, "pct": 11.8}, {"src": "stuck", "tgt": "broke", "count": 1, "pct": 5.9}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 5.9}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 5.9}, {"src": "stay", "tgt": "end_limit", "count": 1, "pct": 5.9}, {"src": "improved", "tgt": "end_limit", "count": 1, "pct": 5.9}, {"src": "churn", "tgt": "churn", "count": 1, "pct": 5.9}]}, {"label": "edge_case", "total": 9, "edges": [{"src": "stay", "tgt": "stay", "count": 6, "pct": 66.7}, {"src": "breakthrough", "tgt": "stay", "count": 2, "pct": 22.2}, {"src": "regressed", "tgt": "churn", "count": 1, "pct": 11.1}]}, {"label": "execute_plan", "total": 12, "edges": [{"src": "stuck", "tgt": "improved", "count": 5, "pct": 41.7}, {"src": "stuck", "tgt": "breakthrough", "count": 3, "pct": 25.0}, {"src": "stay", "tgt": "stay", "count": 1, "pct": 8.3}, {"src": "breakthrough", "tgt": "stay", "count": 1, "pct": 8.3}, {"src": "broke", "tgt": "stuck", "count": 1, "pct": 8.3}, {"src": "broke", "tgt": "breakthrough", "count": 1, "pct": 8.3}]}, {"label": "explore", "total": 51, "edges": [{"src": "stuck", "tgt": "stuck", "count": 13, "pct": 25.5}, {"src": "start", "tgt": "stuck", "count": 13, "pct": 25.5}, {"src": "stay", "tgt": "broke", "count": 7, "pct": 13.7}, {"src": "broke", "tgt": "stuck", "count": 5, "pct": 9.8}, {"src": "stay", "tgt": "stay", "count": 4, "pct": 7.8}, {"src": "stuck", "tgt": "broke", "count": 3, "pct": 5.9}, {"src": "improved", "tgt": "broke", "count": 2, "pct": 3.9}, {"src": "start", "tgt": "improved", "count": 1, "pct": 2.0}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 2.0}, {"src": "stuck", "tgt": "improved", "count": 1, "pct": 2.0}, {"src": "breakthrough", "tgt": "broke", "count": 1, "pct": 2.0}]}, {"label": "fix_bug", "total": 55, "edges": [{"src": "stay", "tgt": "stay", "count": 20, "pct": 36.4}, {"src": "breakthrough", "tgt": "stay", "count": 6, "pct": 10.9}, {"src": "stuck", "tgt": "stuck", "count": 4, "pct": 7.3}, {"src": "stuck", "tgt": "breakthrough", "count": 4, "pct": 7.3}, {"src": "improved", "tgt": "regressed", "count": 4, "pct": 7.3}, {"src": "stuck", "tgt": "improved", "count": 3, "pct": 5.5}, {"src": "improved", "tgt": "improved", "count": 3, "pct": 5.5}, {"src": "improved", "tgt": "stuck", "count": 2, "pct": 3.6}, {"src": "improved", "tgt": "breakthrough", "count": 2, "pct": 3.6}, {"src": "broke", "tgt": "improved", "count": 1, "pct": 1.8}, {"src": "improved", "tgt": "churn", "count": 1, "pct": 1.8}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 1.8}, {"src": "broke", "tgt": "breakthrough", "count": 1, "pct": 1.8}, {"src": "regressed", "tgt": "breakthrough", "count": 1, "pct": 1.8}, {"src": "regressed", "tgt": "churn", "count": 1, "pct": 1.8}, {"src": "regressed", "tgt": "improved", "count": 1, "pct": 1.8}]}, {"label": "implement", "total": 162, "edges": [{"src": "start", "tgt": "breakthrough", "count": 73, "pct": 45.1}, {"src": "stay", "tgt": "stay", "count": 35, "pct": 21.6}, {"src": "breakthrough", "tgt": "stay", "count": 12, "pct": 7.4}, {"src": "start", "tgt": "improved", "count": 9, "pct": 5.6}, {"src": "stuck", "tgt": "stuck", "count": 6, "pct": 3.7}, {"src": "stuck", "tgt": "improved", "count": 5, "pct": 3.1}, {"src": "improved", "tgt": "stuck", "count": 4, "pct": 2.5}, {"src": "start", "tgt": "stuck", "count": 4, "pct": 2.5}, {"src": "breakthrough", "tgt": "regressed", "count": 3, "pct": 1.9}, {"src": "stuck", "tgt": "breakthrough", "count": 2, "pct": 1.2}, {"src": "regressed", "tgt": "improved", "count": 2, "pct": 1.2}, {"src": "stuck", "tgt": "regressed", "count": 2, "pct": 1.2}, {"src": "broke", "tgt": "improved", "count": 1, "pct": 0.6}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 0.6}, {"src": "broke", "tgt": "breakthrough", "count": 1, "pct": 0.6}, {"src": "improved", "tgt": "breakthrough", "count": 1, "pct": 0.6}, {"src": "improved", "tgt": "regressed", "count": 1, "pct": 0.6}]}, {"label": "infra_confusion", "total": 5, "edges": [{"src": "stay", "tgt": "stay", "count": 3, "pct": 60.0}, {"src": "stay", "tgt": "end_submit", "count": 1, "pct": 20.0}, {"src": "stay", "tgt": "broke", "count": 1, "pct": 20.0}]}, {"label": "optimize_perf", "total": 66, "edges": [{"src": "stay", "tgt": "stay", "count": 39, "pct": 59.1}, {"src": "breakthrough", "tgt": "stay", "count": 17, "pct": 25.8}, {"src": "stuck", "tgt": "breakthrough", "count": 3, "pct": 4.5}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 1.5}, {"src": "stuck", "tgt": "stuck", "count": 1, "pct": 1.5}, {"src": "broke", "tgt": "stuck", "count": 1, "pct": 1.5}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 1.5}, {"src": "improved", "tgt": "improved", "count": 1, "pct": 1.5}, {"src": "improved", "tgt": "breakthrough", "count": 1, "pct": 1.5}, {"src": "stay", "tgt": "regressed", "count": 1, "pct": 1.5}]}, {"label": "revert", "total": 24, "edges": [{"src": "stay", "tgt": "stay", "count": 14, "pct": 58.3}, {"src": "stuck", "tgt": "stuck", "count": 8, "pct": 33.3}, {"src": "improved", "tgt": "stuck", "count": 1, "pct": 4.2}, {"src": "churn", "tgt": "breakthrough", "count": 1, "pct": 4.2}]}, {"label": "rewrite", "total": 26, "edges": [{"src": "stuck", "tgt": "stuck", "count": 7, "pct": 26.9}, {"src": "stuck", "tgt": "improved", "count": 3, "pct": 11.5}, {"src": "breakthrough", "tgt": "stay", "count": 2, "pct": 7.7}, {"src": "broke", "tgt": "improved", "count": 2, "pct": 7.7}, {"src": "churn", "tgt": "broke", "count": 2, "pct": 7.7}, {"src": "broke", "tgt": "breakthrough", "count": 2, "pct": 7.7}, {"src": "improved", "tgt": "regressed", "count": 2, "pct": 7.7}, {"src": "stuck", "tgt": "broke", "count": 1, "pct": 3.8}, {"src": "regressed", "tgt": "stuck", "count": 1, "pct": 3.8}, {"src": "stay", "tgt": "broke", "count": 1, "pct": 3.8}, {"src": "improved", "tgt": "breakthrough", "count": 1, "pct": 3.8}, {"src": "regressed", "tgt": "regressed", "count": 1, "pct": 3.8}, {"src": "regressed", "tgt": "improved", "count": 1, "pct": 3.8}]}, {"label": "verify", "total": 121, "edges": [{"src": "breakthrough", "tgt": "end_submit", "count": 40, "pct": 33.1}, {"src": "stay", "tgt": "end_submit", "count": 31, "pct": 25.6}, {"src": "stay", "tgt": "stay", "count": 20, "pct": 16.5}, {"src": "stay", "tgt": "end_limit", "count": 10, "pct": 8.3}, {"src": "stuck", "tgt": "end_submit", "count": 6, "pct": 5.0}, {"src": "stuck", "tgt": "end_limit", "count": 5, "pct": 4.1}, {"src": "stuck", "tgt": "stuck", "count": 3, "pct": 2.5}, {"src": "improved", "tgt": "end_limit", "count": 3, "pct": 2.5}, {"src": "breakthrough", "tgt": "stay", "count": 1, "pct": 0.8}, {"src": "regressed", "tgt": "end_limit", "count": 1, "pct": 0.8}, {"src": "improved", "tgt": "end_submit", "count": 1, "pct": 0.8}]}], "n_problems": 100, "max_count": 225, "lang": "python", "model_scope": "gemma"};

	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>