{"id":"W2275439971","doi":"10.1007/978-3-642-38326-7_36","title":"Learning to Identify Inappropriate Antimicrobial Prescriptions","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Abstraction; Medical prescription; Artificial intelligence; Interval (graph theory); Data mining; Machine learning; Representation (politics); Function (biology); Raw data; Rule induction; Medicine; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009796032,0.0005274666,0.00039095,0.0004487543,0.000164098,0.000647133,0.0006577016,0.0005585771,0.004350839],"category_scores_gemma":[0.006684852,0.0001691941,0.0003972004,0.0003122313,0.000209201,0.0009348485,0.0006020853,0.001148922,0.001113634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000360968,"about_ca_system_score_gemma":0.0006729323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001621514,"about_ca_topic_score_gemma":0.002993509,"domain_scores_codex":[0.9997051,0.00009801595,0.00002405069,0.0000742242,0.00007502748,0.00002343051],"domain_scores_gemma":[0.9968946,0.002341961,0.0001786802,0.0001434393,0.0003751087,0.00006614032],"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":[0.00009399585,0.0002890415,0.01022619,0.0001142603,0.00007804496,0.00004657674,0.00009806141,0.04669536,0.001082969,0.003206116,0.01613458,0.9219348],"study_design_scores_gemma":[0.00004620282,0.0003487278,0.005806155,0.0001685222,0.00009834555,0.0001919971,0.0002131718,0.9277861,0.004194234,0.05014767,0.01096623,0.00003268522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1410421,0.002988652,0.7988741,0.01042042,0.0005476286,0.0001870787,0.00173504,0.002997066,0.04120794],"genre_scores_gemma":[0.7694219,0.001863234,0.2079047,0.001483744,0.0004771834,0.0001484061,0.001938173,0.0000701362,0.01669256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004350839,"threshold_uncertainty_score":0.01455504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729735707791987,"score_gpt":0.2439283421095389,"score_spread":0.226630985031619,"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."}}