{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006159504,0.0005167316,0.0004646928,0.002279212,0.0004325763,0.001259806,0.00169187,0.0007560895,0.002320392],"category_scores_gemma":[0.01156714,0.00008924596,0.0003784739,0.002430188,0.001123685,0.001344242,0.0008225897,0.002627065,0.001050342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482221,"about_ca_system_score_gemma":0.001928803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004013483,"about_ca_topic_score_gemma":0.004377454,"domain_scores_codex":[0.9980789,0.0007558013,0.0002028512,0.0001734025,0.0006323224,0.0001566308],"domain_scores_gemma":[0.996824,0.0009057282,0.0004950934,0.000208344,0.001263986,0.0003028186],"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":[0.000210657,0.00002714838,0.02812662,0.0005964427,0.00005374282,0.0009484037,0.0004474743,0.001481034,0.001677704,0.08508377,0.1402412,0.7411059],"study_design_scores_gemma":[0.00005220377,0.0002686427,0.03965239,0.001704074,0.0001205411,0.01751294,0.0007829875,0.008276219,0.001099196,0.1167998,0.8136758,0.0000553087],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.1021395,0.3459277,0.1707549,0.1894421,0.04260378,0.0005633226,0.003684,0.001446384,0.1434383],"genre_scores_gemma":[0.6286586,0.1063673,0.1620964,0.03915953,0.02436727,0.0007699455,0.00584312,0.000691782,0.03204598],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006159504,"threshold_uncertainty_score":0.03257495,"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."}}