{"id":"W4318917048","doi":"10.1097/pai.0000000000001087","title":"The Biomarker Ki-67: Promise, Potential, and Problems in Breast Cancer","year":2022,"lang":"en","type":"review","venue":"Applied immunohistochemistry & molecular morphology","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biomarker; Breast cancer; Context (archaeology); Medicine; Ki-67; Cancer; Oncology; Confounding; Selection (genetic algorithm); Internal medicine; Immunohistochemistry; Computer science; Biology; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003098939,0.000944301,0.001250344,0.0000990985,0.0004479829,0.00005887287,0.0008583842,0.0006157214,0.000146829],"category_scores_gemma":[0.00002614098,0.0007872138,0.0004072299,0.0003368851,0.000724254,0.000003615449,0.001191015,0.0006825631,0.000009666122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000403347,"about_ca_system_score_gemma":0.0005041258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002011519,"about_ca_topic_score_gemma":0.000002215718,"domain_scores_codex":[0.9964352,0.0001881694,0.0008241889,0.001446868,0.0002805095,0.000825097],"domain_scores_gemma":[0.9979482,0.00005617908,0.0005528222,0.00127845,0.00005309186,0.0001112155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002428976,0.0002771101,0.00003107367,0.002934782,0.001950245,0.0001913549,0.00004743298,0.00001448802,0.5220118,0.00005039173,0.003106996,0.4691414],"study_design_scores_gemma":[0.00181808,0.00005950468,0.0002356919,0.0006451412,0.001237783,0.002656989,0.00009809471,0.000001287059,0.001308416,0.00007544855,0.9903986,0.001464923],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003043527,0.9939325,0.00001886266,0.0002110194,0.00031021,0.001329356,0.0003174033,0.00003124856,0.0008058543],"genre_scores_gemma":[0.00607343,0.9852096,0.00005197125,0.0001656673,0.0001056798,0.006836629,0.001040808,0.0001825354,0.0003336691],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9872916,"threshold_uncertainty_score":0.9994579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393818256281828,"score_gpt":0.2870864789852649,"score_spread":0.2731482964224466,"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."}}