{"id":"W7075904940","doi":"10.6084/m9.figshare.c.7985512","title":"Individual-level characteristics and geospatial factors associated with cervical cancer screening participation in Alberta, Canada: a population-based cross-sectional study","year":2025,"lang":"en","type":"other","venue":"Figshare","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"","keywords":"Cervical cancer; Cervical cancer screening; Public health; Cancer screening; Geospatial analysis; Logistic regression; Cervical screening; Descriptive statistics; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008240595,0.0004232656,0.000423431,0.001612806,0.00236677,0.001337392,0.001319421,0.0005347533,0.001842633],"category_scores_gemma":[0.001748661,0.0004335896,0.0005804304,0.004655545,0.0007762312,0.0003274288,0.0007808651,0.0006101246,0.0002585159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0143166,"about_ca_system_score_gemma":0.01686435,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.989222,"about_ca_topic_score_gemma":0.9912993,"domain_scores_codex":[0.9990909,0.00008221322,0.00005783341,0.0001562551,0.0003727475,0.0002399248],"domain_scores_gemma":[0.9984848,0.0001380593,0.0002877453,0.00007535714,0.0006246692,0.0003894995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003337942,0.00003661184,0.9979115,0.00001561551,0.00003579178,0.00005334689,0.0002993193,0.00006980324,0.00007838097,0.00002624873,0.0003417541,0.001098216],"study_design_scores_gemma":[0.000004061089,0.00001904105,0.998448,0.0000141925,0.00002309843,0.00003610576,0.0009090255,0.0002490008,0.00002171812,0.00001313574,0.0002567222,0.000005780217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951667,0.00035517,0.0001123213,0.0001237173,0.000007831024,0.00005475178,0.002890805,0.00001083658,0.001277969],"genre_scores_gemma":[0.9972525,0.0002607851,0.0002212011,0.00007465969,0.00000497947,0.00002466003,0.001365457,0.000003599126,0.0007921582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0143166,"threshold_uncertainty_score":0.1038747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06359753546546493,"score_gpt":0.3076387179824266,"score_spread":0.2440411825169617,"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."}}