{"id":"W4224255507","doi":"10.1016/j.ypmed.2022.107055","title":"Racial/ethnic inequalities in cervical cancer screening in the United States: An outcome reclassification to better inform interventions and benchmarks","year":2022,"lang":"en","type":"article","venue":"Preventive Medicine","topic":"Cervical Cancer and HPV Research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Medicine; Ethnic group; Psychological intervention; Poisson regression; Cervical cancer; Demography; Inequality; Cancer screening; Cancer; Gerontology; Environmental health; Population; Internal medicine; Psychiatry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002436003,0.0001360715,0.0003408472,0.0007000295,0.0001218986,0.00001451632,0.0002069521,0.00004022651,0.006242521],"category_scores_gemma":[0.0003207664,0.00009562231,0.00005723391,0.001400569,0.0001321109,0.0001121692,0.0001961774,0.0007525724,0.00000168314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000217611,"about_ca_system_score_gemma":0.00005310354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006306665,"about_ca_topic_score_gemma":0.008929498,"domain_scores_codex":[0.9976795,0.0005021745,0.0006146117,0.0002757567,0.000623368,0.0003046198],"domain_scores_gemma":[0.9991108,0.0002918163,0.00007973184,0.0002534536,0.0001193569,0.0001448061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001410342,0.0005803899,0.5978896,0.0007716055,0.00008399069,0.00006173983,0.08685014,0.0001989781,0.00008394342,0.0009347733,0.001477559,0.3096569],"study_design_scores_gemma":[0.002277714,0.0009887894,0.9584011,0.0002193631,0.0000518042,0.000006867491,0.02963142,0.001653085,0.000007317302,0.0006179032,0.006036847,0.0001077545],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9543266,0.001101208,0.0008735274,0.04086151,0.0001025039,0.001273631,0.00004365322,0.00001854529,0.001398797],"genre_scores_gemma":[0.9918106,0.0001760471,0.0000796197,0.005860117,0.0001453656,0.0008422768,0.0007057708,0.00001365637,0.0003666022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3605116,"threshold_uncertainty_score":0.9946659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2485985889917853,"score_gpt":0.4788014626049274,"score_spread":0.2302028736131421,"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."}}