{"id":"W2178073088","doi":"","title":"Government prescribing errors.","year":2008,"lang":"en","type":"article","venue":"PubMed Central","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Computer science; Data science; Medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003420341,0.0006213475,0.0003751948,0.001304076,0.001222414,0.001417191,0.0008145862,0.002599258,0.6304784],"category_scores_gemma":[0.005595387,0.0004123726,0.0003800814,0.001490758,0.0004196393,0.001349787,0.001152032,0.001708624,0.5164928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009572898,"about_ca_system_score_gemma":0.00282899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02897618,"about_ca_topic_score_gemma":0.06079969,"domain_scores_codex":[0.9992035,0.00006252377,0.00005531065,0.00006191769,0.000496671,0.0001200631],"domain_scores_gemma":[0.9957787,0.0006226863,0.000505826,0.0002067222,0.002119251,0.0007668432],"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":[0.000007946642,0.000006600909,0.0001018888,0.00002726239,5.54396e-7,0.00003080117,0.000007884605,0.000006750875,0.00002273101,0.0001715834,0.9802633,0.01935278],"study_design_scores_gemma":[0.00001846177,0.000008842138,0.001547111,0.000109611,0.000001979623,0.0001198349,0.00004417798,0.00004854932,0.00007070888,0.0002484238,0.9977754,0.000006994066],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0008127117,0.001539056,0.0004185925,0.05238827,0.01170932,0.0002017025,0.01429207,0.002349346,0.9162889],"genre_scores_gemma":[0.00576551,0.001922654,0.0007691028,0.03203239,0.002602849,0.00009665897,0.006220631,0.0004440909,0.9501461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6304784,"threshold_uncertainty_score":0.5270777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07476282676868076,"score_gpt":0.3382100031449914,"score_spread":0.2634471763763107,"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."}}