{"id":"W1592777669","doi":"10.1007/bf03405441","title":"Immigrant women and cervical cancer screening uptake: a multilevel analysis.","year":2008,"lang":"en","type":"article","venue":"PubMed","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Immigration; Pap test; Demography; Cervical cancer; Multilevel model; Census; Marital status; Ethnic group; Logistic regression; Neighbourhood (mathematics); Metropolitan area; Public health; Medicine; American Community Survey; Gerontology; Geography; Environmental health; Cancer; Cervical cancer screening; Population; Sociology; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00163202,0.0003270045,0.000784611,0.001293462,0.0007892757,0.0009160654,0.0008544127,0.0009787403,0.005785886],"category_scores_gemma":[0.007543852,0.0003304286,0.002959613,0.002466157,0.0003296561,0.0007217034,0.001567768,0.001436144,0.0003016309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005822207,"about_ca_system_score_gemma":0.001373659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07767241,"about_ca_topic_score_gemma":0.07280204,"domain_scores_codex":[0.9981128,0.0009335718,0.000145244,0.0002233636,0.0001729449,0.0004119585],"domain_scores_gemma":[0.9961255,0.002048085,0.0008072906,0.0002959632,0.000299041,0.0004241706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004481618,0.00006020998,0.9916286,0.0001905802,0.00274716,0.0001392096,0.0004290009,0.0002088636,0.00009474872,0.0002172297,0.001010779,0.002825455],"study_design_scores_gemma":[0.0000700237,0.0003819425,0.9896194,0.0002430968,0.003156259,0.0002260968,0.002782097,0.001962143,0.00009619512,0.0003025795,0.001131594,0.00002853241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905391,0.003014216,0.0003612954,0.0008787555,0.00004745574,0.00004738659,0.003554322,0.00001767563,0.001539762],"genre_scores_gemma":[0.9982626,0.0004670494,0.0001850945,0.00008832938,0.00001878952,0.00004986847,0.0005765509,0.00000646849,0.0003452967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07767241,"threshold_uncertainty_score":0.1544406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09950078075368934,"score_gpt":0.3043415265966837,"score_spread":0.2048407458429943,"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."}}