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@@ -78,7 +78,17 @@ Evaluated with Leave-One-Source-Out (LOSO) cross-validation — each source doma
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  | qualitative_interview | 78 | 0.650 | 0.560 | 0.842 |
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  | **macro-avg** | — | **0.655** | 0.718 | 0.727 |
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- Batch regression against 95 curated hard cases (Pidgin idioms, dialect, regulatory register, clinical shorthand, minimal pairs): **85/95 pass (89.5%)**.
 
 
 
 
 
 
 
 
 
 
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  ## Training Data
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  | qualitative_interview | 78 | 0.650 | 0.560 | 0.842 |
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  | **macro-avg** | — | **0.655** | 0.718 | 0.727 |
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+ **Model status:** Pilot model built and actively improved through iterative research phases.
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+ >
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+ > **Evaluation methodology:** Leave-One-Source-Out (LOSO) — each source domain is held out entirely
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+ > during training and evaluated as an unseen genre. This is the headline generalization metric above
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+ > (macro CLF F1 = 0.724, macro NER F1 = 0.655).
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+ >
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+ > We also maintain an internal, evolving suite of curated hard cases (Pidgin, dialect, regulatory
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+ > register, clinical shorthand, minimal pairs) used to diagnose and target specific model weaknesses
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+ > during development. It's a diagnostic tool, not a benchmark — we don't publish a fixed pass-rate from
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+ > it here, since the suite and the model are both still changing, and a fixed percentage risks reading as
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+ > a settled result rather than a snapshot of an active development target.
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  ## Training Data
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