{"id":"W6995905866","doi":"","title":"Prévention des évènements indésirables liés aux médicaments grâce au bilan des médicaments, aux divers points de transition du patient à l'hôpital","year":2011,"lang":"fr","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Patient rights; Patient Empowerment; Digital era","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":[],"consensus_categories":[],"category_scores_codex":[0.002994985,0.0003356196,0.0005402525,0.001428839,0.001087976,0.00206027,0.0006499689,0.0009880672,0.007350452],"category_scores_gemma":[0.01267735,0.000228174,0.0005857389,0.0009425195,0.0006122024,0.0008110111,0.0020082,0.001138081,0.0008880499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411797,"about_ca_system_score_gemma":0.004752982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005184909,"about_ca_topic_score_gemma":0.007641685,"domain_scores_codex":[0.9973495,0.001245356,0.0001804362,0.0001942373,0.0006241768,0.0004062006],"domain_scores_gemma":[0.9926541,0.001678963,0.003338397,0.0003126446,0.001115456,0.0009004814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001300534,0.00125193,0.2795673,0.002752021,0.0003377507,0.00244322,0.004942452,0.0004232974,0.003991679,0.0106323,0.01295325,0.6794043],"study_design_scores_gemma":[0.000234909,0.007158857,0.7281489,0.01029221,0.0007580838,0.007378039,0.008798611,0.001260857,0.009265813,0.006842863,0.2197284,0.0001324869],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.810671,0.09568791,0.009179988,0.02381832,0.0009479511,0.0007221776,0.0007954013,0.0002908476,0.05788641],"genre_scores_gemma":[0.9351628,0.03791971,0.008022191,0.002542776,0.0003741516,0.0004239634,0.000416468,0.00004621574,0.01509162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007350452,"threshold_uncertainty_score":0.02458966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05470432632121595,"score_gpt":0.3512452260477677,"score_spread":0.2965408997265517,"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."}}