{"id":"W3185795980","doi":"","title":"Rapport d’avancement AMCER n° 1 : \"Acquisition, Modélisation, Capitalisation et Evaluation des Risques\". Application au domaine de la sécurité des transports ferroviaires","year":2019,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mod; Humanities; Geology; Computer science; Art; Artificial intelligence","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":[0.04196288,0.002060175,0.001874138,0.003344283,0.001662883,0.008065458,0.00291332,0.005649165,0.05589532],"category_scores_gemma":[0.1213842,0.0008637588,0.003353079,0.002318809,0.001285872,0.004140566,0.004009316,0.00420629,0.01468461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005782357,"about_ca_system_score_gemma":0.01360661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03318228,"about_ca_topic_score_gemma":0.01657441,"domain_scores_codex":[0.9731492,0.01483153,0.001397702,0.002132365,0.007650947,0.0008383298],"domain_scores_gemma":[0.8817642,0.05618458,0.003523778,0.008399068,0.04743345,0.002694938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001682045,0.0004476164,0.006077545,0.003478324,0.0004148992,0.0005076487,0.001595089,0.03073407,0.003894814,0.06060582,0.6774918,0.2130703],"study_design_scores_gemma":[0.0005998244,0.0009137762,0.01465626,0.004933214,0.0003311776,0.0003730611,0.001083863,0.04209473,0.01488876,0.05506537,0.8647276,0.000332547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.05967811,0.03131441,0.405239,0.1715862,0.06937622,0.007665204,0.04914946,0.009582565,0.1964088],"genre_scores_gemma":[0.2405225,0.01786467,0.3638615,0.01727582,0.01361302,0.01008147,0.05236508,0.006992089,0.2774239],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05589532,"threshold_uncertainty_score":0.2219235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05256355508707509,"score_gpt":0.3724146234538755,"score_spread":0.3198510683668004,"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."}}