{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001242852,0.0006629185,0.001402257,0.002575955,0.0003248955,0.001382151,0.001014045,0.001395625,0.002177244],"category_scores_gemma":[0.002299213,0.0002881624,0.0004986203,0.00307676,0.0008076479,0.002148772,0.0007718233,0.002525476,0.001745811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009945125,"about_ca_system_score_gemma":0.001788797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001691465,"about_ca_topic_score_gemma":0.003135916,"domain_scores_codex":[0.9996358,0.00008686823,0.00005903145,0.00005974758,0.0001310856,0.00002752453],"domain_scores_gemma":[0.9987896,0.0006928604,0.0001043539,0.00002761582,0.0003249416,0.00006069559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006758346,0.0000335721,0.0002117056,0.02047762,0.00007033341,0.0001948353,0.00009802503,0.0002582734,0.0007909001,0.006091217,0.0476401,0.9240659],"study_design_scores_gemma":[0.000007505007,0.00005985428,0.0006168333,0.006182621,0.00006833051,0.0009507742,0.0001081519,0.00005837004,0.0001785089,0.002799215,0.9889511,0.00001886289],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003798736,0.9987248,0.00004764323,0.0005806398,0.0002903192,0.000001073277,0.000007611439,0.000002683798,0.000307161],"genre_scores_gemma":[0.0002284446,0.999051,0.00008219943,0.0002554501,0.0001861886,0.000002139405,0.00001107332,8.925966e-7,0.0001825823],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002575955,"threshold_uncertainty_score":0.007283568,"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."}}