{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002996742,0.0002412092,0.0005686448,0.0002110749,0.0005958353,0.0001035131,0.0001217303,0.00005450778,0.00004637759],"category_scores_gemma":[0.0002271166,0.0001818325,0.00003742972,0.0009433693,0.0001543686,0.000165145,0.0001696346,0.0005863665,5.270313e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004111462,"about_ca_system_score_gemma":0.001339214,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003685706,"about_ca_topic_score_gemma":0.03364578,"domain_scores_codex":[0.9966516,0.001181981,0.0004498612,0.0005484856,0.0005940701,0.0005739879],"domain_scores_gemma":[0.9986566,0.000392537,0.000243956,0.0002683728,0.0001311106,0.0003074689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001924881,0.0001390458,0.9704149,0.0001723016,0.00003095152,0.00001503156,0.004296672,0.000004900142,0.000002388459,0.00002088516,0.001011188,0.0219668],"study_design_scores_gemma":[0.002194356,0.007209719,0.9680667,0.00002664172,0.000001411661,0.00009743877,0.006967784,0.0001155942,7.662056e-7,0.00001365885,0.01509371,0.0002122503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878526,0.005087744,0.0001018681,0.004476827,0.0001575179,0.002000641,0.00007158224,0.0001336533,0.0001175576],"genre_scores_gemma":[0.9967279,0.0003236552,0.00004335937,0.0008160185,0.0001292306,0.001239124,0.00004540903,0.00002960554,0.0006457249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02996007,"threshold_uncertainty_score":0.9839877,"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."}}