{"id":"W2582664561","doi":"","title":"EVALUATING COLORECTAL CANCER SCREENING OPTIONS FOR CANADA USING ONCOSIM","year":2016,"lang":"en","type":"article","venue":"38th Annual North American Meeting of the Society for Medical Decision Making","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Colorectal cancer; Medicine; Cancer; Business; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001570903,0.000401849,0.0004605038,0.002481904,0.00113258,0.00155128,0.0008285748,0.0003998518,0.004453979],"category_scores_gemma":[0.0121408,0.0002014376,0.0008128227,0.002753897,0.0003458182,0.0004832464,0.0006357266,0.0004909605,0.0004426204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01672127,"about_ca_system_score_gemma":0.03413822,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8668367,"about_ca_topic_score_gemma":0.9614631,"domain_scores_codex":[0.9988232,0.0002673435,0.0001025271,0.00007300155,0.0005016843,0.0002323117],"domain_scores_gemma":[0.9954875,0.001204184,0.0004176113,0.00005363234,0.002176794,0.0006602162],"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":[0.001547433,0.0003504306,0.8708729,0.0002509057,0.0003025923,0.0003379293,0.000336351,0.001968083,0.0002597893,0.0006962103,0.01481952,0.1082579],"study_design_scores_gemma":[0.0005093818,0.0009170918,0.9351698,0.0005413702,0.001235554,0.0007208225,0.003070091,0.02725227,0.00173285,0.001058403,0.02770272,0.00008973733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524732,0.004076389,0.001115234,0.006380721,0.0001036415,0.0005213776,0.008777381,0.0001510603,0.026401],"genre_scores_gemma":[0.9848424,0.002095517,0.005389259,0.0008959393,0.00003474037,0.0001059574,0.003393331,0.00003061817,0.003212154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1331633,"threshold_uncertainty_score":0.267895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07117297278273181,"score_gpt":0.4193558507861945,"score_spread":0.3481828780034626,"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."}}