{"id":"W2605957788","doi":"10.70675/ce66a07fzf1d6z43b4zbb0dz612a3fc04135","title":"Approche textométrique et comparative du discours de segmentation du marché automobile : implications pour la traduction publicitaire anglais > français","year":2017,"lang":"fr","type":"dissertation","venue":"","topic":"Linguistics and Discourse Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy; Art","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":[0.002017465,0.0005103825,0.0004058285,0.006159997,0.001576427,0.004673659,0.0007223877,0.0006368449,0.01446437],"category_scores_gemma":[0.007628956,0.0003442985,0.0004038619,0.008925937,0.001699549,0.002518866,0.001030542,0.0007632959,0.001917149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005010631,"about_ca_system_score_gemma":0.002869979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2034099,"about_ca_topic_score_gemma":0.2275449,"domain_scores_codex":[0.9986913,0.0004488154,0.00009132842,0.0002603802,0.0003934429,0.0001147322],"domain_scores_gemma":[0.9946529,0.00227895,0.000715644,0.0002951148,0.001931367,0.0001259637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000512647,0.00009892093,0.2591227,0.001893664,0.0002017047,0.0006221709,0.1598174,0.00617529,0.02087738,0.1462533,0.01574812,0.3886767],"study_design_scores_gemma":[0.00002880797,0.0001331629,0.54444,0.0008461786,0.0001942924,0.0005615827,0.1379743,0.01942522,0.008319264,0.02014729,0.267712,0.0002178198],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7662298,0.00386276,0.08118557,0.004152001,0.0001662605,0.0001857036,0.00620019,0.0004699185,0.1375478],"genre_scores_gemma":[0.9487229,0.001314438,0.02274313,0.0001032451,0.00005250294,0.0001777388,0.001901964,0.0001948261,0.02478929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2034099,"threshold_uncertainty_score":0.4044517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03817902864788965,"score_gpt":0.3294759471799091,"score_spread":0.2912969185320194,"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."}}