{"id":"W2977709247","doi":"10.1002/cam4.2026","title":"Impact on immigrant screening adherence with introduction of a population‐based colon screening program in Ontario, Canada","year":2019,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"University of British Columbia","keywords":"Immigration; Medicine; Guideline; Logistic regression; Population; Cancer screening; Intervention (counseling); Demography; Gerontology; Family medicine; Environmental health; Cancer; Internal medicine; Nursing; Geography; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001350177,0.0001589254,0.0002576443,0.0004507884,0.001880545,0.0007749996,0.0008448573,0.0003391632,0.002031773],"category_scores_gemma":[0.006070987,0.0001551608,0.0006024176,0.001318056,0.0006580628,0.0002892345,0.0009254391,0.0005387366,0.00009972279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0238229,"about_ca_system_score_gemma":0.05373108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9873755,"about_ca_topic_score_gemma":0.9920362,"domain_scores_codex":[0.9984078,0.0002656683,0.00008283478,0.0001204767,0.0006437949,0.0004794672],"domain_scores_gemma":[0.995617,0.0003588318,0.001078698,0.0001084053,0.001316458,0.001520552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001518203,0.00009036706,0.9846726,0.00009108833,0.00006575089,0.0001064607,0.001098371,0.0001466195,0.0001759267,0.0001178674,0.001441078,0.01184213],"study_design_scores_gemma":[0.000009696758,0.00005920005,0.9979341,0.00005109309,0.00002443253,0.00002542927,0.0007591374,0.000127284,0.00003055738,0.00001164561,0.0009619477,0.000005504924],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915711,0.0007535917,0.0001079433,0.002006183,0.00003025811,0.00007357999,0.001153718,0.0000154028,0.004288209],"genre_scores_gemma":[0.9976761,0.0005044342,0.0001965774,0.0003033516,0.0000109545,0.00002924857,0.0004668131,0.000004071855,0.0008085415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0238229,"threshold_uncertainty_score":0.172848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809884153261996,"score_gpt":0.292558239850812,"score_spread":0.274459398318192,"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."}}