{"id":"W2592303973","doi":"10.1158/1538-7445.sabcs16-p1-03-01","title":"Abstract P1-03-01: An international multicenter study to evaluate reproducibility of automated scoring methods for assessment of Ki67 in breast cancer","year":2017,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Juravinski Hospital; Mount Sinai Hospital; Ontario Institute for Cancer Research","funders":"","keywords":"Reproducibility; Intraclass correlation; Medicine; Breast cancer; Nuclear proliferation; Medical physics; Cancer; Biopsy; Nuclear medicine; Pathology; Statistics; Mathematics; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.01584716,0.0001029074,0.0003858974,0.0002648795,0.0001133723,0.0000468125,0.0004991834,0.00003584389,0.0002633511],"category_scores_gemma":[0.003339477,0.00008578576,0.00005855547,0.0001359558,0.0001727375,0.0001610475,0.0002389782,0.000489798,6.210914e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004603717,"about_ca_system_score_gemma":0.0005152095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01201521,"about_ca_topic_score_gemma":0.0003743898,"domain_scores_codex":[0.9974388,0.0003123266,0.0004769951,0.0007543466,0.0006944098,0.0003230654],"domain_scores_gemma":[0.9972701,0.0002322225,0.0001825186,0.00136879,0.0007679304,0.0001784013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006840203,0.0009197711,0.7794078,0.000282482,0.0001261938,0.00000708917,0.001008568,0.0009150617,0.1175135,0.000009900622,0.0001379235,0.09898763],"study_design_scores_gemma":[0.002362484,0.0001962763,0.8969678,0.0005192716,0.00002579257,0.000001020676,0.0002954651,0.09409505,0.005322974,0.00002133669,0.0001277799,0.00006470249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935539,0.0000541201,0.0003048054,0.003803583,0.0004520263,0.001447211,0.00003586304,0.00002196348,0.0003265095],"genre_scores_gemma":[0.9870495,0.00005486073,0.01219856,0.00004202115,0.000222383,0.000324659,0.000005969539,0.00002364566,0.0000784452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.11756,"threshold_uncertainty_score":0.9945639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2166136544018778,"score_gpt":0.6358156388975048,"score_spread":0.419201984495627,"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."}}