{"id":"W4291992223","doi":"10.2196/34589","title":"Colorectal Cancer Incidence, Inequalities, and Prevention Priorities in Urban Texas: Surveillance Study With the “surveil” Software Package","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incidence (geometry); Software package; Cancer; Software; Medicine; Environmental health; Computer science; Internal medicine; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001888371,0.0005022321,0.0003426539,0.001549701,0.0003246385,0.0007811509,0.0009458101,0.0002115089,0.006253628],"category_scores_gemma":[0.008012623,0.0004403105,0.0008176301,0.001933124,0.0001628834,0.0005680394,0.001314788,0.0005700393,0.001149441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008657991,"about_ca_system_score_gemma":0.002992183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05007752,"about_ca_topic_score_gemma":0.05730627,"domain_scores_codex":[0.9993748,0.0002560547,0.0000756868,0.0001435526,0.00009310586,0.00005675317],"domain_scores_gemma":[0.9973456,0.001029556,0.000744037,0.0003098365,0.000366901,0.0002040735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003987054,0.0002733109,0.8117244,0.0005023193,0.0003776271,0.000184426,0.001304565,0.01184929,0.0003629973,0.001531979,0.1149215,0.05656886],"study_design_scores_gemma":[0.0003842659,0.0005681983,0.8339337,0.0006031853,0.0006292795,0.0005529362,0.002324508,0.09340652,0.001554907,0.002635951,0.06328104,0.0001256171],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6105923,0.0004346778,0.05002687,0.00217421,0.00007300406,0.001946211,0.3113114,0.0105205,0.01292077],"genre_scores_gemma":[0.72199,0.0005281004,0.1166698,0.0004244928,0.00009361884,0.006125687,0.1472528,0.001215021,0.005700489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05007752,"threshold_uncertainty_score":0.09957206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02783288057022529,"score_gpt":0.3081536341927954,"score_spread":0.2803207536225701,"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."}}