{"id":"W2140966604","doi":"10.1002/jso.21282","title":"Standardized synoptic cancer pathology reporting: A population‐based approach","year":2009,"lang":"en","type":"article","venue":"Journal of Surgical Oncology","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":204,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McMaster University; Cancer Care Ontario","funders":"","keywords":"Medicine; Cancer; Population; Pathology; Environmental health; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001813488,0.0001561683,0.001222752,0.0002774145,0.00003689576,0.00001380087,0.0001078521,0.0001796153,0.0001697065],"category_scores_gemma":[0.00114932,0.0001071302,0.0002788717,0.00028378,0.0001184959,0.0001123473,0.00001500836,0.0006144387,0.000003368091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004679615,"about_ca_system_score_gemma":0.0006909771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006380987,"about_ca_topic_score_gemma":4.830097e-7,"domain_scores_codex":[0.9970084,0.000133705,0.001822905,0.0001920292,0.0005356756,0.0003072429],"domain_scores_gemma":[0.9966426,0.0002420412,0.002099894,0.0001923188,0.0005056912,0.0003174268],"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":[0.01496201,0.006550719,0.2005702,0.0003026546,0.0005942928,0.1375493,0.0004845737,0.002595316,0.006918004,0.001936441,0.02581356,0.6017229],"study_design_scores_gemma":[0.0350224,0.01547992,0.2437075,0.0008587131,0.00137569,0.1161115,0.0002411694,0.002380689,0.0005700694,0.002525339,0.5811861,0.0005409642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8934021,0.001285444,0.002908087,0.03742783,0.000819241,0.0003146795,0.00000369456,0.00005968481,0.06377927],"genre_scores_gemma":[0.9804369,0.0001510368,0.01585685,0.002408349,0.0007007889,0.000003777344,0.00001061162,0.00001587358,0.0004158157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.601182,"threshold_uncertainty_score":0.4368644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04724715972314162,"score_gpt":0.3941274780859888,"score_spread":0.3468803183628472,"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."}}