{"id":"W2034417342","doi":"10.7202/037220ar","title":"Les noms propres et leurs dérivés dans le vocabulaire de l’intelligence artificielle","year":2007,"lang":"fr","type":"article","venue":"TTR traduction terminologie rédaction","topic":"linguistics and terminology studies","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007316534,0.000458835,0.0003995898,0.0002858707,0.001879281,0.0002295482,0.0002822088,0.0004174148,0.0002562745],"category_scores_gemma":[0.0002190937,0.00046207,0.0002253944,0.0001074103,0.002064192,0.0003611715,0.00008429723,0.0007372823,0.0001456609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005169748,"about_ca_system_score_gemma":0.0001639256,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051196,"about_ca_topic_score_gemma":0.004344969,"domain_scores_codex":[0.997284,0.0001758485,0.0007267997,0.0006612574,0.0002420582,0.000910053],"domain_scores_gemma":[0.9986244,0.0002217867,0.0003610982,0.0004240156,0.0002443858,0.0001243286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001563293,0.001029882,0.003513165,0.0002552299,0.0002785725,0.0002341522,0.03362289,0.0005296892,0.002149615,0.48841,0.002611069,0.4672094],"study_design_scores_gemma":[0.0006166865,0.001180694,0.05173273,0.0002863999,0.0004817206,0.0007947036,0.07789472,0.001791081,0.0732244,0.02991716,0.7606111,0.001468574],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8585364,0.006031567,0.03568843,0.009411449,0.01344367,0.0006170447,0.00007751676,0.000788829,0.07540509],"genre_scores_gemma":[0.9371896,0.002101934,0.00046433,0.0001509806,0.002418878,0.00003443512,0.00003355318,0.00005681463,0.05754942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7580001,"threshold_uncertainty_score":0.9997831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1967704696037403,"score_gpt":0.3335090919504706,"score_spread":0.1367386223467302,"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."}}