{"id":"W6944250147","doi":"10.17863/cam.116011","title":"Lessons learned from a candidate gene study investigating aromatase inhibitor treatment outcome in breast cancer.","year":2025,"lang":"en","type":"article","venue":"Apollo (University of Cambridge)","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Cancer Institute; Department of Health and Social Care; National Institutes of Health; Ovarian Cancer Research Fund; Fondation du cancer du sein du Québec; Canadian Institutes of Health Research; National Institute for Health and Care Research; Genome Canada; Cancer Research UK; Government of Canada; NIHR Cambridge Biomedical Research Centre; European Commission; Breast Cancer Research Foundation","keywords":"Aromatase inhibitor; Breast cancer; Candidate gene; Meta-analysis; Germline; Aromatase; Cancer; Germline mutation; Linkage (software)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006887484,0.0001969987,0.0003645909,0.0001141645,0.0001481811,0.000009440459,0.0001667536,0.00007537816,0.000009870133],"category_scores_gemma":[0.00001438317,0.0002173239,0.0001091899,0.0002284861,0.0001305481,0.000009783605,0.0001976259,0.00005910276,0.000003861681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001983068,"about_ca_system_score_gemma":0.0002324067,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07100257,"about_ca_topic_score_gemma":0.01561523,"domain_scores_codex":[0.9989774,0.00008318164,0.0001698428,0.0004458264,0.000107016,0.000216796],"domain_scores_gemma":[0.999386,0.00003031431,0.0001201684,0.0003496131,0.00004556744,0.0000683929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003490709,0.0005130918,0.9601043,0.00001807503,0.0006470174,0.00004583678,0.0007082135,0.00004729801,0.02693392,0.00002458077,0.00133058,0.009277968],"study_design_scores_gemma":[0.003913936,0.000100025,0.980049,0.00007746419,0.0002458039,0.000002546934,0.004375919,0.00002850456,0.01017983,0.00001496153,0.000794742,0.0002172431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936481,0.000501624,0.00003614288,0.003941577,0.0001027988,0.0002605688,0.001353359,0.00001571972,0.0001401696],"genre_scores_gemma":[0.998484,0.0003858616,0.000199857,0.0001000488,0.00004760376,0.000006564626,0.0002236485,0.00001066247,0.0005418172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05538735,"threshold_uncertainty_score":0.9351837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02961495410212636,"score_gpt":0.2902788781705085,"score_spread":0.2606639240683821,"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."}}