{"id":"W2404127287","doi":"10.1158/1538-7445.sabcs15-s4-06","title":"Abstract S4-06: HER2 status as predictive marker for AI vs Tam benefit: A TRANS-AIOG meta-analysis of 12129 patients from ATAC, BIG 1-98 and TEAM with centrally determined HER2","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Medicine; Tamoxifen; Oncology; Biomarker; Meta-analysis; Clinical trial; Internal medicine; Breast cancer; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02473577,0.00244507,0.01068168,0.002090376,0.000538752,0.003145145,0.002145501,0.002058423,0.007449191],"category_scores_gemma":[0.02405914,0.001168188,0.05338196,0.002694456,0.0005108232,0.00140144,0.001710863,0.003407391,0.0008729863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001421186,"about_ca_system_score_gemma":0.001430712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006068864,"about_ca_topic_score_gemma":0.008031296,"domain_scores_codex":[0.9846269,0.01107123,0.001434367,0.001522644,0.0009466485,0.0003982463],"domain_scores_gemma":[0.9800931,0.01407704,0.00215867,0.001687581,0.00135367,0.0006299556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.02803237,0.00005207691,0.01816708,0.01537184,0.9297874,0.0001257258,0.00006357442,0.001990002,0.0005709532,0.0001742307,0.002940499,0.002724259],"study_design_scores_gemma":[0.005557299,0.0007659639,0.01653968,0.0008889468,0.9717155,0.00009844624,0.00005926227,0.001654749,0.0002299935,0.0005222281,0.001921769,0.0000462571],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.435091,0.4692092,0.01869923,0.005590886,0.00379984,0.002875074,0.05787155,0.000838547,0.006024643],"genre_scores_gemma":[0.9694796,0.01045017,0.004136309,0.001990153,0.0004008526,0.001632186,0.00953497,0.0002017472,0.002174112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02473577,"threshold_uncertainty_score":0.1308168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04502783810296389,"score_gpt":0.3771822604092702,"score_spread":0.3321544223063063,"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."}}