{"id":"W2766298867","doi":"10.4000/traduire.907","title":"La traduction médicale : des nomenclatures à l’orthographe, petit florilège des pièges et difficultés","year":2017,"lang":"fr","type":"article","venue":"Traduire","topic":"Medical and Biological Sciences","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Historical Studies in Education","funders":"","keywords":"Philosophy; Humanities","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001089841,0.0003434072,0.0004862045,0.00006252928,0.001164029,0.0002314913,0.0005668562,0.0005004589,0.002174732],"category_scores_gemma":[0.0009368101,0.0002091906,0.0002916726,0.0002255323,0.008190986,0.0004096521,0.00009371585,0.0006939621,0.0001242778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006115441,"about_ca_system_score_gemma":0.0001076202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003986717,"about_ca_topic_score_gemma":0.0003089409,"domain_scores_codex":[0.9973359,0.0002985807,0.0003816216,0.0005976433,0.0005619679,0.0008243421],"domain_scores_gemma":[0.9982328,0.0002728525,0.0001761213,0.00045198,0.00006712102,0.0007990616],"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":[0.0001424592,0.001106589,0.2244061,0.0005742415,0.0001052535,0.000267643,0.001366857,0.000001306482,0.004608351,0.02268066,0.00362755,0.741113],"study_design_scores_gemma":[0.0008456395,0.0007555554,0.8692024,0.0009885601,0.0001377455,0.0001845135,0.000632598,0.00006057905,0.0003652443,0.009547524,0.116985,0.0002946103],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9184613,0.02408721,0.0002678415,0.02154947,0.002471487,0.000315166,0.00005200803,0.0001296262,0.03266592],"genre_scores_gemma":[0.9692026,0.01578226,0.001250276,0.0004323549,0.002037702,0.00002402465,0.00002385267,0.00001508585,0.01123181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7408184,"threshold_uncertainty_score":0.9987374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07758622784066185,"score_gpt":0.346623113548945,"score_spread":0.2690368857082832,"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."}}