{"id":"W2889799971","doi":"10.23889/ijpds.v3i4.925","title":"Cancer Screening in the Toronto Central LHIN by Sub-region and Neighbourhood: Evidence from an Applied Health Research Question (AHRQ)","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Medicine; Family medicine; Immigration; Cancer screening; Psychological intervention; Cervical cancer; Health care; Population; Cancer; Cervical cancer screening; Neighbourhood (mathematics); Demography; Gerontology; Environmental health; Nursing; Geography; Internal medicine; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00443391,0.00009198538,0.0001249124,0.000127583,0.0005788496,0.0004392219,0.00107156,0.00003886596,0.00004279087],"category_scores_gemma":[0.0007718827,0.00006889925,0.00001753407,0.0002731562,0.0002515874,0.003326317,0.0001592589,0.0002557589,0.000001017175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005746874,"about_ca_system_score_gemma":0.0003728253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0549903,"about_ca_topic_score_gemma":0.02357649,"domain_scores_codex":[0.997108,0.0001304599,0.0003669955,0.0004365884,0.001575217,0.0003827858],"domain_scores_gemma":[0.9985272,0.000160207,0.0002017672,0.000326049,0.0005685846,0.0002161637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001267,0.00009055206,0.5690173,0.00001053757,0.00002677346,0.00001318286,0.002719805,0.0001429969,0.00569233,0.002984619,0.01031114,0.4077238],"study_design_scores_gemma":[0.0006349158,0.0002838019,0.9618737,0.0006760515,0.000009987641,0.00009724596,0.001029124,0.03198415,0.0002426345,0.0009458994,0.002123736,0.00009872362],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950905,0.00174214,0.0304974,0.01518219,0.0008847466,0.0005269804,0.0001574315,0.00001633171,0.00008784238],"genre_scores_gemma":[0.993013,0.0007679037,0.003274986,0.001495415,0.001185342,0.00001288907,0.0002315123,0.000006640239,0.00001226257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4076251,"threshold_uncertainty_score":0.9942407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3894744167739918,"score_gpt":0.554729586927895,"score_spread":0.1652551701539032,"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."}}