{"id":"W1589076019","doi":"","title":"Comprendre le vernaculaire pour s’intégrer","year":2011,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Linguistic and Sociocultural Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"INT; Computer science","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":[0.003071812,0.001569592,0.0005115714,0.001109594,0.005480738,0.009075307,0.001176178,0.002453721,0.03162325],"category_scores_gemma":[0.007438927,0.0004206837,0.0005747979,0.00111538,0.003706582,0.00439602,0.002549914,0.004822132,0.007628271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006666092,"about_ca_system_score_gemma":0.0103458,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1790534,"about_ca_topic_score_gemma":0.1481706,"domain_scores_codex":[0.9958225,0.001941599,0.0001772931,0.000446429,0.001228407,0.0003837358],"domain_scores_gemma":[0.9975673,0.0004090501,0.0001194323,0.0003082282,0.001314877,0.0002812012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004284248,0.0001738082,0.005017353,0.0003832004,0.00007390796,0.00175153,0.03465064,0.0007435697,0.02620918,0.5239201,0.1247547,0.2818936],"study_design_scores_gemma":[0.00002494636,0.00005763299,0.003024801,0.0001640887,0.00001753928,0.0004162429,0.006383033,0.0005404209,0.00360801,0.004659952,0.9810503,0.0000530134],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1499726,0.01865616,0.1148771,0.09436092,0.04111603,0.000465463,0.001221674,0.002686343,0.5766438],"genre_scores_gemma":[0.3558283,0.004187378,0.03426867,0.005632578,0.003011258,0.0002777003,0.0006827149,0.001592896,0.5945185],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8209466,"threshold_uncertainty_score":0.3560224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974442865406515,"score_gpt":0.1907546610194321,"score_spread":0.1710102323653669,"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."}}