{"id":"W2921980052","doi":"10.1200/jco.2015.33.15_suppl.e17734","title":"Predictors of attrition in the treatment of metastatic colorectal cancer (MCRC).","year":2015,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Colorectal Cancer Treatments and Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Medicine; Cohort; Colorectal cancer; Attrition; Cancer; Internal medicine; Logistic regression; Confounding; Population; Disease; Proportional hazards model; Medical record; Cohort study; Oncology","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":[0.004101898,0.0001799758,0.00045216,0.0006005501,0.0005426218,0.0005567383,0.0007339669,0.0005473812,0.002414264],"category_scores_gemma":[0.01712113,0.0001977452,0.001014946,0.001368677,0.0002409415,0.0005985239,0.000796358,0.001429633,0.0003122977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007558297,"about_ca_system_score_gemma":0.001250611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051075,"about_ca_topic_score_gemma":0.01471508,"domain_scores_codex":[0.9979776,0.0006135904,0.0002835186,0.0001974931,0.0005420626,0.0003858078],"domain_scores_gemma":[0.9855117,0.004237474,0.007603281,0.0004979745,0.0012059,0.0009435568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001532043,0.00002040559,0.9977795,0.00001378536,0.00002464257,0.00002632992,0.00002271217,0.00008676872,0.00001351069,0.000009848714,0.0002072544,0.001642052],"study_design_scores_gemma":[0.00001518974,0.0001122203,0.99756,0.00002649754,0.00003673291,0.0001594053,0.00009741048,0.001386338,0.00003764437,0.00004273064,0.0005214442,0.000004360916],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963433,0.0007739854,0.0002180971,0.0005650676,0.0000116548,0.00003950372,0.001456877,0.000007568701,0.0005840474],"genre_scores_gemma":[0.9981055,0.0001714828,0.0001774245,0.0000981263,0.0000194498,0.0000257098,0.001166286,0.000003923611,0.000232132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01051075,"threshold_uncertainty_score":0.02169317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2627255436798661,"score_gpt":0.5101945243127587,"score_spread":0.2474689806328926,"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."}}