{"id":"W2726395676","doi":"10.1016/s1470-2045(17)30438-2","title":"The TNM classification of malignant tumours—towards common understanding and reasonable expectations","year":2017,"lang":"en","type":"article","venue":"The Lancet Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":286,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"National Cancer Institute; National Institutes of Health; World Health Organization","keywords":"CLARITY; Profiling (computer programming); Disease; Medicine; Cancer; Pathology; Internal medicine; Computer science; Biology","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":[0.0009450258,0.00005699241,0.0002397619,0.00001870775,0.0006903283,0.00003884675,0.0002110194,0.00004357284,0.000007237186],"category_scores_gemma":[0.0005776716,0.00002991407,0.00002750759,0.00002846249,0.0005848614,0.00003330339,0.00006282112,0.0002562542,0.000002455798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008883668,"about_ca_system_score_gemma":0.00008958207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001623072,"about_ca_topic_score_gemma":0.00009306016,"domain_scores_codex":[0.9993519,0.0001182516,0.0001488323,0.00009992558,0.0001132456,0.0001678916],"domain_scores_gemma":[0.99895,0.0003363049,0.0002185986,0.0004165744,0.00003241486,0.00004609321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0008335382,0.0001940122,0.2413366,0.0001734164,0.0002374001,0.00006617209,0.006297978,0.00001768853,0.01757106,0.5205835,0.02576925,0.1869195],"study_design_scores_gemma":[0.002902955,0.0004000122,0.9016418,0.0001678012,0.0001969469,0.0002613093,0.007933341,0.0210456,0.0003767317,0.02579669,0.0391599,0.0001168428],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7148263,0.0006945445,0.001738046,0.2373168,0.0003340839,0.0002663116,0.000003237742,0.00003045864,0.0447902],"genre_scores_gemma":[0.9980209,0.0005439545,0.0005035645,0.0003091188,0.000242642,0.00001341602,0.000003792068,0.000008043946,0.0003545779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6603053,"threshold_uncertainty_score":0.5309517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1075127998060665,"score_gpt":0.3980224307440145,"score_spread":0.290509630937948,"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."}}