{"id":"W2622614052","doi":"10.4000/hommesmigrations.3828","title":"Du burkini au bleu de travail","year":2017,"lang":"fr","type":"article","venue":"Hommes & migrations","topic":"Multiculturalism, Politics, Migration, Gender","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"BLEU; Computer science; Natural language processing; Machine translation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00108157,0.000342891,0.0001928153,0.0005226327,0.007266994,0.004134936,0.0003128361,0.001408498,0.02437784],"category_scores_gemma":[0.001662078,0.000155818,0.00009007323,0.0008393076,0.00161095,0.00166018,0.001735053,0.001522947,0.003343608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005685227,"about_ca_system_score_gemma":0.004498621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09708322,"about_ca_topic_score_gemma":0.1505497,"domain_scores_codex":[0.999101,0.0004099557,0.00002392428,0.00011294,0.0001331364,0.0002189521],"domain_scores_gemma":[0.9989724,0.0002599161,0.0001134081,0.00007351727,0.0002230568,0.0003577735],"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":[0.0007445851,0.0002472708,0.03447143,0.001031362,0.00003930714,0.009301278,0.1585759,0.0003951019,0.01150683,0.2973569,0.2068374,0.2794927],"study_design_scores_gemma":[0.000005138098,0.00003406372,0.01266244,0.0002139726,0.000003647055,0.000573003,0.0288569,0.00006838264,0.0008008927,0.001685203,0.9550813,0.00001497691],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2773957,0.06772426,0.001726387,0.103876,0.002896981,0.0001208059,0.0005844635,0.0001167981,0.5455586],"genre_scores_gemma":[0.5504569,0.01305663,0.00103106,0.006978882,0.0003729015,0.00005385092,0.0001562521,0.00004779406,0.4278457],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09708322,"threshold_uncertainty_score":0.1930363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119787295276749,"score_gpt":0.3884747520187096,"score_spread":0.2764960224910347,"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."}}