{"id":"W7028037355","doi":"","title":"Données massives en hygiène du travail, exploitation des banques de mesures d'exposition professionnelle","year":2017,"lang":"fr","type":"article","venue":"","topic":"Occupational exposure and asthma","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Risk management; Vulnerability (computing)","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":[0.01520913,0.0008237188,0.0009961434,0.004939632,0.00310606,0.003362713,0.001383567,0.002722919,0.006718628],"category_scores_gemma":[0.05439194,0.0005411266,0.001296856,0.004164988,0.002800683,0.00209157,0.002470393,0.002498244,0.001146003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003460005,"about_ca_system_score_gemma":0.007847613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1138681,"about_ca_topic_score_gemma":0.1812444,"domain_scores_codex":[0.9864357,0.003794666,0.001736415,0.001011072,0.006323877,0.0006982342],"domain_scores_gemma":[0.952235,0.029061,0.005903653,0.002881533,0.008706025,0.001212692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002282886,0.0004544545,0.2191495,0.01317636,0.0009699663,0.007810037,0.04624429,0.0008167036,0.02743017,0.01490313,0.1390837,0.5276788],"study_design_scores_gemma":[0.0000994795,0.0007123752,0.2478322,0.007155448,0.0005955812,0.009066191,0.02224911,0.0004579003,0.01468466,0.009270715,0.6875628,0.0003136269],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4463568,0.1896655,0.03322206,0.2030465,0.01228006,0.001123573,0.02198679,0.001370981,0.09094774],"genre_scores_gemma":[0.7568295,0.08663866,0.04206987,0.03043498,0.004270232,0.0005672589,0.006338393,0.0004299933,0.07242107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1138681,"threshold_uncertainty_score":0.2264106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798920399017808,"score_gpt":0.3318247668917054,"score_spread":0.3038355629015274,"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."}}