{"id":"W2402154038","doi":"10.3233/978-1-61499-432-9-1260","title":"Reduce Medication Errors by Applying a Probabilistic Model: A Pilot Study","year":2014,"lang":"en","type":"article","venue":"Medical Informatics Europe","topic":"Pharmaceutical Practices and Patient Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Probabilistic logic; Reliability engineering; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001806938,0.0002093647,0.0003776651,0.00008710141,0.0001194181,0.00003666045,0.000282706,0.00006309612,0.0002610918],"category_scores_gemma":[0.003816667,0.0001512864,0.00004151974,0.0002973974,0.0001557033,0.0002641552,0.0001147869,0.0006854599,0.0003185236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004576074,"about_ca_system_score_gemma":0.0001511599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001436661,"about_ca_topic_score_gemma":0.000002720574,"domain_scores_codex":[0.9968477,0.0001638146,0.0009196173,0.0001743284,0.001536316,0.0003581656],"domain_scores_gemma":[0.9980446,0.0003918019,0.0002572287,0.0004161768,0.0001375898,0.0007525969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006908914,0.05449446,0.09220092,0.01046705,0.001973393,0.0002345187,0.05283881,0.00501885,0.002626754,0.01406974,0.2872731,0.4718935],"study_design_scores_gemma":[0.003176576,0.002557567,0.0003853048,0.0001361601,0.0002313151,0.00004392007,0.0003183048,0.9345942,0.0000346017,0.0001051251,0.05820001,0.0002168863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8896723,0.0000652107,0.04431257,0.00470478,0.0004404465,0.002895457,0.000008315715,0.0003581171,0.0575428],"genre_scores_gemma":[0.9906341,0.00005108707,0.001526232,0.006941395,0.0001110608,0.0001144099,0.0000470527,0.00003036926,0.0005443133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9295754,"threshold_uncertainty_score":0.6169282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1401886917698867,"score_gpt":0.3953001605256328,"score_spread":0.2551114687557461,"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."}}