Align card with ORR-only, AUC-only, and BioBench release

README.md

@@ -16,61 +16,39 @@ The public benchmark release is separated by evaluation scale. Each notebook
 is fully executed, explains every reported score, and links its compact
 evaluation script and input tables.
 
-- **[Cohort-level benchmarks](https://github.com/alunalabs/GAIA/blob/main/01_cohort_level_benchmarks.ipynb):** drug perturbation priors, the shared gene-readout efficacy score, all 44 trial ORRs and their source ledger, a separate ORR-calibrated output, comparisons, and controls.
-- **[Patient-level benchmarks](https://github.com/alunalabs/GAIA/blob/main/02_patient_level_benchmarks.ipynb):** the same four-gate score applied to CRC and cSCC, exact label controls, cSCC terminal-readout audits, and CRC measured on-treatment biology.
-- **[Biology-level benchmarks](https://github.com/alunalabs/GAIA/blob/main/03_biology_level_benchmarks.ipynb):** the 289-row CellChatBench protocol, row inventories, exact scoring rules, worked examples, and results.
+- **[Cohort-level benchmarks](https://github.com/alunalabs/gaia/blob/main/01_cohort_level_benchmarks.ipynb):** drug perturbation priors, the complete 44-row trial-ORR source ledger, direct predicted-versus-observed ORR comparisons, and controls.
+- **[Patient-level benchmarks](https://github.com/alunalabs/gaia/blob/main/02_patient_level_benchmarks.ipynb):** the current CRC and cSCC patient-response scores, ROC AUC evaluation, exact label controls, and CRC measured on-treatment biology.
+- **[Biology-level benchmarks](https://github.com/alunalabs/gaia/blob/main/03_biology_level_benchmarks.ipynb):** the 289-row BioBench protocol, exact KO/OE scoring rules, row-family inventory, and KO gene-direction audit.
 
 The complete benchmark package is in the
-**[public Gaia GitHub repository](https://github.com/alunalabs/GAIA)**.
-
-## Shared gene-readout efficacy score
-
-The cohort, CRC, and cSCC evaluations use the same final arithmetic:
-
-```text
-bio_conversion_support = mean(response_conversion_support,
-                              terminal_efficacy_support)
-
-universal_gene_readout_score = coverage_support
-                               * bio_conversion_support
-                               * resistant_tail_control
-```
-
-The terminal readout is therapy-aware: cohort and CRC use apoptosis support;
-cSCC checkpoint blockade uses control of persistent immune escape. The score
-is unitless and is not a calibrated clinical response probability or ORR.
+**[public Gaia GitHub repository](https://github.com/alunalabs/gaia)**.
 
 ## Released results
 
 | Evaluation | Result |
 | --- | --- |
-| Cohort universal gene-readout efficacy, 44 disease–drug rows | Pearson 0.658; Spearman 0.626 |
-| Separate cohort ORR-calibrated output, same 44 rows | Pearson 0.650; Spearman 0.594; MAE 10.25 ORR percentage points |
-| CRC shared-formula response, 11 patients | ROC AUC 0.800; Spearman 0.520; exact p=0.0628 |
-| cSCC shared-formula response, 12 patients | ROC AUC 0.778; Spearman 0.483; exact p=0.0660 |
-| Previous cSCC-specific five-axis comparator, same patients | ROC AUC 0.944; Spearman 0.772 |
+| Cohort ORR, 44 disease–drug rows | Pearson 0.650; Spearman 0.594; MAE 10.25 ORR percentage points |
+| CRC pretreatment response, 11 patients | ROC AUC 0.800 |
+| cSCC pretreatment response, 12 patients | ROC AUC 0.778 |
 | CRC measured on-treatment biology, 11 patients | Best descriptive mean cosine 0.304 at rollout step 4 |
-| CellChatBench sender knockout | 257/289 direction passes (88.9%) |
-| CellChatBench sender overexpression | 257/281 scoreable direction passes (91.5%); 8 rows not applicable |
-
-The previous cSCC-specific score is shown because it discriminates better, but
-it is not the cross-benchmark headline. Enforcing the shared formula reduces
-cSCC AUC from 0.944 to 0.778; this is the cost of comparability, not an
-improvement. A strict literal-apoptosis cSCC audit reaches AUC 0.417 and is not
-presented as a supported checkpoint terminal mechanism.
+| BioBench sender knockout | 257/289 direction passes (88.9%) |
+| BioBench sender overexpression | 257/281 scoreable direction passes (91.5%); 8 rows not applicable |
+| BioBench KO gene-direction audit | 0/173 audited ligand rows had every observed pathway gene decrease; median fraction decreasing 61.9% |
 
-The CellChatBench release contains 183 ligand–receptor pathway rows and 106
-regional tissue-program rows. All released knockout statements expect a
-receiver decrease and all overexpression statements expect an increase, so
-these results do not establish inhibitory-sign balance.
+BioBench contains 183 ligand–receptor pathway rows and 106 regional
+tissue-program rows. The separate per-gene audit is available for 173 ligand
+rows. It rules out an all-pathway-genes-down explanation on those rows, not all
+possible global-shift confounding; 10 ligand rows and the 106 regional rows do
+not have the same archived gene-level audit.
 
 ## Reproduction boundary
 
-The GitHub release reproduces formulas, aggregation, metrics, controls, tables,
-and figures from compact exported benchmark data. It contains evaluation
-scripts only—no model training code—and does not rerun upstream spatial
-inference. Raw tissue assays, source perturbation matrices, full per-cell
-outputs, checkpoints, and model weights are not included.
+The GitHub release reproduces metrics, controls, tables, and figures from
+compact exported benchmark data. A public model-adapter runner owns the cohort,
+patient, and BioBench orchestration and score construction; the actual model,
+weights, tissue loader, and encoder remain behind the adapter. The included
+released-table adapter is explicitly a deterministic smoke test, not fresh
+inference. The repository contains no training code.
 
 This Hugging Face repository currently contains the project card only; model
 weights are not currently published here.
@@ -81,7 +59,7 @@ validation or a clinical decision system.
 ## License
 
 Repository-authored release material is available under
-[CC BY-NC 4.0](https://github.com/alunalabs/GAIA/blob/main/LICENSE). Commercial
+[CC BY-NC 4.0](https://github.com/alunalabs/gaia/blob/main/LICENSE). Commercial
 use is not permitted under that license. Underlying publications, study
 records, databases, and source datasets retain their own terms.