{"id":"W2906119240","doi":"","title":"Online predictive diagnosis of electrical train door systems","year":2013,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bombardier (Canada)","funders":"","keywords":"Train; Probabilistic logic; Discriminative model; Computer science; Closing (real estate); Machine learning; Artificial intelligence; Binary classification; Segmentation; Support vector machine","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":[0.0002976547,0.000553209,0.0004903137,0.0005463317,0.0001482047,0.0005188571,0.0005681041,0.0005045352,0.0008323209],"category_scores_gemma":[0.001464672,0.0001944351,0.0002916722,0.0003131934,0.0002650068,0.0003816332,0.000507431,0.0006098052,0.0002186997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002639971,"about_ca_system_score_gemma":0.0002609961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002224447,"about_ca_topic_score_gemma":0.002017471,"domain_scores_codex":[0.9997734,0.00003554885,0.00001031434,0.0000758034,0.00006085035,0.00004398761],"domain_scores_gemma":[0.99942,0.0003564493,0.00008791364,0.00004036026,0.00006589321,0.00002932916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006041645,0.0002068428,0.008742535,0.0001795065,0.00004535364,0.0005490616,0.0001655781,0.702939,0.0394802,0.002331463,0.001382197,0.2433741],"study_design_scores_gemma":[0.000003497139,0.00002303931,0.001880325,0.000003540981,0.000003955071,0.00005026929,0.00001201889,0.9944099,0.002841183,0.0006186061,0.0001496803,0.000004035094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.218678,0.0003817745,0.7778095,0.0001350842,0.0000400618,0.00003374127,0.000231893,0.001436718,0.001253208],"genre_scores_gemma":[0.9840942,0.00008001077,0.01488925,0.00001787471,0.00001864362,0.00001510372,0.0001850417,0.00002605064,0.0006737902],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002224447,"threshold_uncertainty_score":0.004423022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008887315817699061,"score_gpt":0.2020115906333959,"score_spread":0.1931242748156968,"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."}}