{"id":"W2401769792","doi":"10.1158/1538-7445.sabcs15-p1-01-01","title":"Abstract P1-01-01: Analytical validation of a standardized scoring protocol for Ki67: Phase-3 of an international multicenter collaboration","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Ontario Institute for Cancer Research","funders":"","keywords":"External quality assessment; Intraclass correlation; Medicine; Breast cancer; Protocol (science); Nuclear proliferation; Nuclear medicine; Pathology; Medical physics; Reproducibility; Statistics; Cancer; Internal medicine; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2287568,0.002621806,0.00160997,0.001684436,0.003636859,0.003415664,0.005837204,0.003753867,0.005583864],"category_scores_gemma":[0.1329788,0.001419584,0.003014684,0.002527275,0.004120995,0.002063503,0.005874367,0.004123028,0.004183344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004483442,"about_ca_system_score_gemma":0.02267142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00433945,"about_ca_topic_score_gemma":0.003363385,"domain_scores_codex":[0.857718,0.1088137,0.007128218,0.006798316,0.01621058,0.003331128],"domain_scores_gemma":[0.7895057,0.03700864,0.02335156,0.05123278,0.08829568,0.01060566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.1132645,0.09595692,0.1824336,0.009530518,0.005296995,0.001012232,0.02006686,0.01818973,0.1497224,0.01473373,0.06048776,0.3293047],"study_design_scores_gemma":[0.05382426,0.2621216,0.3897437,0.00430203,0.003283533,0.001006827,0.005680019,0.01419007,0.1209172,0.004845893,0.1395289,0.0005560089],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"empirical","genre_scores_codex":[0.3601438,0.001832307,0.1584611,0.002458329,0.001160957,0.4491353,0.008347698,0.001004773,0.01745565],"genre_scores_gemma":[0.3688447,0.0008825971,0.2587393,0.001866286,0.0004375525,0.3400865,0.02288104,0.001063317,0.00519862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2287568,"threshold_uncertainty_score":0.9510801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1148386551603719,"score_gpt":0.5499462012080074,"score_spread":0.4351075460476356,"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."}}