{"id":"W2470655036","doi":"","title":"How complete are drug history profiles that are based on public drug benefit claims?","year":2008,"lang":"en","type":"article","venue":"PubMed","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences","funders":"","keywords":"Medicine; Medical prescription; Prior authorization; Authorization; Family medicine; Drug; Prescription drug; Subsidy; Medical emergency; Actuarial science; Business; Pharmacology; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002516275,0.0002292146,0.0003914269,0.0001858421,0.0001478356,0.00002733711,0.0002789262,0.00007483123,0.0006271729],"category_scores_gemma":[0.0002097876,0.0001952108,0.0001253388,0.000188443,0.000203647,0.0001634897,0.00003056959,0.000331215,0.0003346113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004011703,"about_ca_system_score_gemma":0.000153675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000145851,"about_ca_topic_score_gemma":0.00001831292,"domain_scores_codex":[0.9980111,0.00006443961,0.0002108386,0.000459418,0.0007382014,0.0005160662],"domain_scores_gemma":[0.9982248,0.00009965582,0.0003095569,0.0007103398,0.0001750352,0.0004806431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001156401,0.0003988603,0.2130861,0.0002186667,0.0000429043,0.0001279411,0.0002116626,0.000002495577,0.00002568579,0.0003262126,0.7688935,0.01655028],"study_design_scores_gemma":[0.001108906,0.00001459499,0.652839,0.00009703307,0.00002080307,0.00002026785,0.0002459227,0.0002450318,0.0002426691,0.00007272432,0.3449087,0.0001842679],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7062485,0.003743082,0.0004439773,0.2359373,0.001867044,0.004775485,0.00009790184,0.0008717844,0.04601494],"genre_scores_gemma":[0.9032559,0.0000652845,0.0001649395,0.009149359,0.0002700887,0.002181019,0.00008552385,0.00003097151,0.0847969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4397529,"threshold_uncertainty_score":0.7960464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1399388684643332,"score_gpt":0.2307416946359936,"score_spread":0.09080282617166044,"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."}}