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Atome LM v2 — SuperESP signed on-device heads + held-out metrics

Browse files
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+ <!doctype html><meta charset=utf-8><title>SuperESP agri</title>
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+ <body style="font-family:system-ui;max-width:720px;margin:2rem auto">
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+ <h2>SuperESP head — agri</h2>
4
+ <p>Held-out accuracy <b>0.953</b> (n=450) ·
5
+ abstention AURC <b>0.0053</b> (oracle 0.0011).</p>
6
+ <h3>Confusion (rows=true, cols=pred)</h3>
7
+ <table style="border-collapse:collapse" border=1 cellpadding=6>
8
+ <tr><th></th><th>healthy</th><th>needs_irrigate</th><th>frost_risk</th><th>pest_favorable</th><th>sensor_fault</th></tr><tr><th>healthy</th><td style="background:rgba(34,139,34,0.97);text-align:center">87</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.03);text-align:center">3</td></tr><tr><th>needs_irrigate</th><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(34,139,34,1.00);text-align:center">90</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td></tr><tr><th>frost_risk</th><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(34,139,34,1.00);text-align:center">90</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td></tr><tr><th>pest_favorable</th><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(34,139,34,1.00);text-align:center">90</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td></tr><tr><th>sensor_fault</th><td style="background:rgba(200,60,60,0.19);text-align:center">17</td><td style="background:rgba(200,60,60,0.01);text-align:center">1</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(200,60,60,0.00);text-align:center">0</td><td style="background:rgba(34,139,34,0.80);text-align:center">72</td></tr></table>
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+ </body>
superesp/reports/agri.md ADDED
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1
+ # SuperESP head report — agri
2
+
3
+ Held-out TEST accuracy: **0.953** (n=450) • abstention AURC **0.0053** (oracle 0.0011, random 0.0467)
4
+
5
+ ## Confusion matrix (rows = true, cols = predicted)
6
+
7
+ | true \\ pred | healthy | needs_irrigate | frost_risk | pest_favorable | sensor_fault |
8
+ |---|---|---|---|---|---|
9
+ | healthy | **87** | 0 | 0 | 0 | 3 |
10
+ | needs_irrigate | 0 | **90** | 0 | 0 | 0 |
11
+ | frost_risk | 0 | 0 | **90** | 0 | 0 |
12
+ | pest_favorable | 0 | 0 | 0 | **90** | 0 |
13
+ | sensor_fault | 17 | 1 | 0 | 0 | **72** |
14
+
15
+ ## Per-class recall
16
+ - healthy: 0.967 (87/90)
17
+ - needs_irrigate: 1.000 (90/90)
18
+ - frost_risk: 1.000 (90/90)
19
+ - pest_favorable: 1.000 (90/90)
20
+ - sensor_fault: 0.800 (72/90)
21
+
22
+ ## Risk vs coverage (abstain on low-margin inputs)
23
+ | coverage | risk |
24
+ |---|---|
25
+ | 0.50 | 0.000 |
26
+ | 0.70 | 0.006 |
27
+ | 0.90 | 0.017 |
28
+ | 1.00 | 0.047 |
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+ {
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+ "head": "sound_scene",
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+ "n_classes": 4,
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+ "classes": [
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+ "quiet",
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+ "alarm",
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+ "glass_break",
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+ "speech_like"
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