{"id":"W2890039732","doi":"10.1038/s41374-018-0123-7","title":"Ki67 reproducibility using digital image analysis: an inter-platform and inter-operator study","year":2018,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"AI in cancer detection","field":"Computer Science","cited_by":140,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Institutes of Health; Rosztoczy Foundation; Breast Cancer Research Foundation","keywords":"Reproducibility; Intraclass correlation; Breast cancer; Medicine; Digital image analysis; Tissue microarray; Standardization; Cancer; Nuclear medicine; Pathology; Radiology; Medical physics; Internal medicine; Computer science; Mathematics; Statistics; Computer vision","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":[0.03299214,0.001228123,0.001394679,0.001830607,0.001250836,0.001983893,0.001299623,0.001158789,0.002484647],"category_scores_gemma":[0.05439978,0.0008057699,0.001650925,0.00168342,0.001645601,0.001309349,0.00211682,0.001114587,0.001392351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008631661,"about_ca_system_score_gemma":0.001067791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001876693,"about_ca_topic_score_gemma":0.002990707,"domain_scores_codex":[0.9646618,0.01509538,0.003713506,0.006514513,0.008979398,0.001035422],"domain_scores_gemma":[0.9092218,0.03955564,0.005704879,0.02132927,0.02286656,0.001321949],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03494441,0.004268296,0.6207528,0.001469511,0.006363752,0.001024558,0.01302993,0.005588029,0.1252886,0.002389951,0.002573619,0.1823066],"study_design_scores_gemma":[0.0008192487,0.01280604,0.8641484,0.0001435208,0.003853643,0.001677316,0.002995861,0.01731919,0.08259955,0.002045977,0.01116376,0.000427384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.914765,0.001580745,0.07426785,0.00009092791,0.0006031129,0.001362682,0.0008308073,0.0005723843,0.005926449],"genre_scores_gemma":[0.9787921,0.0001845342,0.01770198,0.0001036664,0.0001001609,0.0006683944,0.0004605083,0.0003776097,0.001610962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9670079,"threshold_uncertainty_score":0.1744812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03432860143619437,"score_gpt":0.2968818050033655,"score_spread":0.2625532035671712,"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."}}