{"id":"W2119545416","doi":"10.1371/journal.pone.0015883","title":"Individual and Contextual Determinants of Regional Variation in Prescription Drug Use: An Analysis of Administrative Data from British Columbia","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; University of British Columbia; Ministry of Health, British Columbia","keywords":"Medical prescription; Proxy (statistics); Prescription drug; Medicine; Health care; Ethnic group; Population; Drug; Environmental health; Logistic regression; Demography; Psychiatry; Pharmacology; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002135989,0.00004199692,0.0002964991,0.00005880672,0.00001721809,0.00003034412,0.0001284837,0.00005990902,0.000613291],"category_scores_gemma":[0.0003542803,0.0000588856,0.00001347048,0.0001948435,0.0001040863,0.0002763444,0.00003650741,0.0001237251,0.000001860006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005659176,"about_ca_system_score_gemma":0.0000947177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02216959,"about_ca_topic_score_gemma":0.1668358,"domain_scores_codex":[0.9990333,0.0000496249,0.0003021667,0.0002263178,0.0003246242,0.00006395467],"domain_scores_gemma":[0.9991313,0.00009767119,0.0002105634,0.0003575749,0.0001332519,0.00006967425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005539546,0.00113947,0.9713302,0.00003074888,0.0003114083,0.000003752617,0.0006117342,6.124814e-8,0.02511714,0.000007893933,0.0003631893,0.001029013],"study_design_scores_gemma":[0.000688094,0.0001023553,0.9915356,0.0001921167,0.0008351152,0.000001518662,0.0002122231,0.005703866,0.0006121261,0.00005657601,0.00001228855,0.00004813889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990042,0.00003009147,0.0000265427,0.00005368622,0.00001245475,0.0002043699,0.0006363599,0.000005865105,0.00002641094],"genre_scores_gemma":[0.9961942,0.00003431978,0.002331066,0.00007804452,0.00002432324,0.00001181765,0.0009946148,0.000003709136,0.000327937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1446662,"threshold_uncertainty_score":0.9843419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2251776675405774,"score_gpt":0.3413752933567246,"score_spread":0.1161976258161472,"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."}}