{"id":"W4390145201","doi":"10.1002/cncr.35155","title":"Data‐driven optimization of version 9 American Joint Committee on Cancer staging system for anal cancer","year":2023,"lang":"en","type":"article","venue":"Cancer","topic":"Colorectal and Anal Carcinomas","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"National Cancer Institute","keywords":"Medicine; Stage (stratigraphy); Cancer; Proportional hazards model; Cancer staging; Survival analysis; Oncology; Anal cancer; AJCC staging system; Internal medicine; Staging system","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":[0.02777572,0.0005124374,0.0005271095,0.001613062,0.0004258357,0.001382032,0.00114787,0.0002354508,0.00147899],"category_scores_gemma":[0.04797772,0.000288308,0.0008421896,0.001956649,0.0004331702,0.0006180816,0.00131901,0.0007934005,0.0005740588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001543163,"about_ca_system_score_gemma":0.004930255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0130027,"about_ca_topic_score_gemma":0.01526546,"domain_scores_codex":[0.9844584,0.009208412,0.001782468,0.001365021,0.002845265,0.0003403238],"domain_scores_gemma":[0.9673043,0.008611438,0.006169837,0.004661554,0.0126313,0.0006216321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008099581,0.000153534,0.7743018,0.0007176262,0.0004752713,0.00009078058,0.000615485,0.01433371,0.003176464,0.002668011,0.02630416,0.1763533],"study_design_scores_gemma":[0.0003082074,0.001036006,0.8052825,0.001349753,0.0005537631,0.0006302234,0.0006104565,0.08726401,0.01168458,0.006051538,0.08502013,0.0002088118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7541423,0.00439829,0.1622587,0.004476822,0.0007143654,0.003863845,0.0475191,0.001975214,0.02065127],"genre_scores_gemma":[0.8369243,0.0009697768,0.1103595,0.0008337094,0.0001657957,0.002594985,0.04589694,0.0003797893,0.001875258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02777572,"threshold_uncertainty_score":0.1468938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07719968965886945,"score_gpt":0.3427930078502065,"score_spread":0.265593318191337,"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."}}