{"id":"W4407787372","doi":"10.1007/s10552-025-01973-w","title":"Integrating healthcare utilization databases for cancer ascertainment in a prospective cohort in a limited resource setting: the Mexican Teachers’ Cohort","year":2025,"lang":"en","type":"article","venue":"Cancer Causes & Control","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"American Institute for Cancer Research","keywords":"Medicine; Epidemiology; Cohort; Limited resources; Public health; Prospective cohort study; Health care; Cohort study; Environmental health; Family medicine; Database; Internal medicine; Nursing; Economic growth","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008658934,0.0002598168,0.0005775385,0.0001935706,0.0001671498,0.00003984249,0.0001757644,0.00009567336,0.00003258901],"category_scores_gemma":[0.000811399,0.000196244,0.00009912889,0.0007610408,0.0001038829,0.0001220653,0.0000456426,0.0004579979,4.979287e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002145833,"about_ca_system_score_gemma":0.001107744,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02903542,"about_ca_topic_score_gemma":0.07588109,"domain_scores_codex":[0.9977846,0.0001759144,0.0005680477,0.0005957234,0.0003482944,0.0005274849],"domain_scores_gemma":[0.9987014,0.0003629234,0.0001895271,0.000386581,0.0002626831,0.00009686686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001000211,0.00005157897,0.9792684,0.0001127108,0.0002005874,0.00001235784,0.001965615,0.0004271174,0.0004607895,0.0008619851,0.001852621,0.01378607],"study_design_scores_gemma":[0.004716233,0.0001651195,0.9558625,0.002666577,0.0003798667,0.000003901517,0.006697257,0.005937745,0.0008957327,0.00009875062,0.02234466,0.0002316153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.916401,0.02578088,0.003525307,0.03952338,0.0004163604,0.01213115,0.0004481872,0.0001519499,0.001621752],"genre_scores_gemma":[0.9834626,0.0004699324,0.0001355727,0.009468039,0.0001810796,0.005871387,0.00008196721,0.00002602023,0.0003034089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06706156,"threshold_uncertainty_score":0.9774303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07577211568375848,"score_gpt":0.4036884139838463,"score_spread":0.3279162983000878,"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."}}