{"id":"W4241744234","doi":"10.1002/cncr.10492.abs","title":"TNM residual tumor classification revisited","year":2002,"lang":"en","type":"article","venue":"Cancer","topic":"Radiopharmaceutical Chemistry and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Classification scheme; Standardization; Residual; Disease; Cancer; Intensive care medicine; Oncology; Internal medicine; Machine learning; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002892228,0.00005269875,0.00008276266,0.00001210249,0.00004321122,0.000006665206,0.00004065775,0.00002926818,0.003512113],"category_scores_gemma":[0.00003071952,0.00004635487,0.00002607141,0.0001421267,0.00004236721,0.00002367196,0.000005240629,0.0001110332,0.0002073738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005677814,"about_ca_system_score_gemma":0.00001343452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001426728,"about_ca_topic_score_gemma":1.325719e-7,"domain_scores_codex":[0.9995618,0.000005785085,0.0001030065,0.0001414626,0.00008766331,0.0001002472],"domain_scores_gemma":[0.9996314,0.00001600901,0.00002706743,0.0001812117,0.00004241141,0.0001019219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005461646,0.0001802344,0.006509457,0.0001731791,0.00004655825,0.00001969792,0.00009087472,0.000004046872,0.7473547,0.002256742,0.2215489,0.02176096],"study_design_scores_gemma":[0.0009167506,0.00002283538,0.03520173,0.00009898796,0.0001325525,0.00004225266,0.00003098813,0.002649151,0.1373185,0.00008779855,0.8233515,0.0001469182],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8182881,0.006106758,0.0001385722,0.03195785,0.00008710402,0.0004701017,0.00003344045,0.0002170369,0.1427011],"genre_scores_gemma":[0.989182,0.0003166097,0.0001530166,0.001667935,0.0004899971,0.00009564621,0.00001467171,0.000008439865,0.008071686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6100362,"threshold_uncertainty_score":0.9973988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1191035021651309,"score_gpt":0.3756598656878826,"score_spread":0.2565563635227517,"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."}}