{"id":"W6886116814","doi":"10.14288/1.0437192","title":"A quantitative assessment of access to medicines in Canada using administrative and survey data","year":2025,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantitative analysis (chemistry); Quantitative assessment; Survey data collection; Survey research; Data collection; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00313455,0.0003979749,0.0004295017,0.007029001,0.002509718,0.002489776,0.001218391,0.0004053674,0.001628227],"category_scores_gemma":[0.01533328,0.0002849835,0.0006731985,0.01873165,0.0008515831,0.0006530355,0.001444603,0.0006035063,0.0002007546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03694652,"about_ca_system_score_gemma":0.05329648,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9900841,"about_ca_topic_score_gemma":0.9875478,"domain_scores_codex":[0.9945654,0.000711585,0.0004099529,0.0004383549,0.003248311,0.0006263292],"domain_scores_gemma":[0.9816036,0.003097103,0.004193582,0.0005926118,0.00912114,0.001391854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006065742,0.00006823801,0.9833325,0.0001352624,0.0001619681,0.00003069329,0.00129758,0.0009317185,0.0001030579,0.0008329376,0.00273682,0.01030864],"study_design_scores_gemma":[0.000007369302,0.00003893645,0.9917092,0.00004461277,0.00002799758,0.00001708346,0.002401339,0.002632351,0.0000740751,0.00009666568,0.002927021,0.0000234153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351727,0.0005399055,0.001259958,0.0009472637,0.00001794903,0.0003515635,0.05324096,0.00005538485,0.008414295],"genre_scores_gemma":[0.9795203,0.0004413054,0.002610342,0.0001575248,0.0000120488,0.0002443793,0.01606088,0.000007410977,0.0009458215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03694652,"threshold_uncertainty_score":0.268067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1920356708689611,"score_gpt":0.3828086774532674,"score_spread":0.1907730065843062,"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."}}