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Oracle reads target scANVI fractions; the separate predictor's training time is unavailable.", + "footnote_full": "Source-only enrichment: saved configs/history + implementation; no new model training, inference or statistical scoring. Validation curves describe internal pretraining-corpus recipes (192 \u00d7 64), not SLE held-out donor scores. Figure 2 benchmark scores remain SLE pseudobulk, not measured bulk\u2013sc paired performance. Architecture and gene-panel families have different detection-floor gene selections and must be compared within family. Training sample fractions are joined by recipe block_id\u2192sample_key. Pred is corpus-trained MLP (train5232/val648/test627 samples), chosen by validation L1 against ridge; log1p(CPM), train-standardized, two hidden GELU/dropout layers and softmax. Oracle aggregates target donor observed AIFI-L1 labels over nine categories. Hint is appended after base G+6, before 2G measurement context; first condition layer 18015\u2192512. Baseline denoiser and hint denoiser are separately trained; pred and oracle share hint denoiser. Predictor params3206153 calculated from recorded architecture, excluded from denoiser count.", + "notes": "Source-only enrichment: saved configs/history + implementation; no new model training, inference or statistical scoring. Validation curves describe internal pretraining-corpus recipes (192 \u00d7 64), not SLE held-out donor scores. Figure 2 benchmark scores remain SLE pseudobulk, not measured bulk\u2013sc paired performance. Architecture and gene-panel families have different detection-floor gene selections and must be compared within family. Training sample fractions are joined by recipe block_id\u2192sample_key. Pred is corpus-trained MLP (train5232/val648/test627 samples), chosen by validation L1 against ridge; log1p(CPM), train-standardized, two hidden GELU/dropout layers and softmax. Oracle aggregates target donor observed AIFI-L1 labels over nine categories. Hint is appended after base G+6, before 2G measurement context; first condition layer 18015\u2192512. Baseline denoiser and hint denoiser are separately trained; pred and oracle share hint denoiser. 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