{"id":"W4412163813","doi":"10.1158/1557-3265.aimachine-b002","title":"Abstract B002: Fairness by Design: End-to-End Bias Evaluation for LLM-Generated Data","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"End-to-end principle; Computer science; End user; Medicine; Computer network; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5485125,0.002712683,0.003819794,0.003398235,0.00315238,0.005974649,0.004533747,0.006575603,0.01987216],"category_scores_gemma":[0.7172812,0.001874208,0.01005912,0.002968357,0.00866984,0.005287043,0.007350171,0.005669508,0.002075322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004575829,"about_ca_system_score_gemma":0.00707812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001940478,"about_ca_topic_score_gemma":0.001607591,"domain_scores_codex":[0.3574557,0.5721915,0.0260974,0.02123216,0.0212165,0.001806707],"domain_scores_gemma":[0.1422447,0.7476436,0.02693826,0.06113704,0.02015128,0.001885198],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.05407885,0.002558422,0.1269367,0.01730106,0.03875398,0.000972249,0.005512228,0.06644472,0.003935309,0.1089361,0.04577843,0.528792],"study_design_scores_gemma":[0.02503281,0.02174989,0.06317176,0.007401663,0.01331345,0.001428619,0.001664526,0.5481739,0.0182519,0.2213822,0.07766701,0.0007623083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04251895,0.001997373,0.9067592,0.002425375,0.001349762,0.03206696,0.004366652,0.00287852,0.005637257],"genre_scores_gemma":[0.3256519,0.0002169883,0.616028,0.001674957,0.0003543608,0.05194653,0.001869039,0.0005790778,0.001679164],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4514875,"threshold_uncertainty_score":0.5567645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.87220080924877,"score_gpt":0.7180107518801088,"score_spread":0.1541900573686612,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}