{"id":"W6931227442","doi":"10.5281/zenodo.4790996","title":"DE LA COMPÉTENCE PRAGMATIQUE EN LANGUE SECONDE: UNE ÉTUDE DES RÉPONSES AUX COMPLIMENTS EN FRANÇAIS L1 ET L2 EN CONTEXTE CANADIEN","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Expansive; Realization (probability); Competence (human resources); Pragmatics; French","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":[0.005551623,0.0008981319,0.0005936015,0.001875885,0.003012587,0.004916878,0.0007732187,0.001844648,0.002283356],"category_scores_gemma":[0.01384446,0.0003605084,0.0007377509,0.001249022,0.004267862,0.002077059,0.001586617,0.002549257,0.0003402121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00929162,"about_ca_system_score_gemma":0.007912605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6339751,"about_ca_topic_score_gemma":0.4327298,"domain_scores_codex":[0.9962621,0.001514929,0.0001412882,0.0003981898,0.001076661,0.0006066493],"domain_scores_gemma":[0.9924356,0.003512701,0.0007999358,0.0001840485,0.002249161,0.0008185309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003128698,0.0004277622,0.2039108,0.0001852662,0.00009294575,0.001457166,0.750058,0.0005712245,0.00710566,0.002254458,0.0006495953,0.03297433],"study_design_scores_gemma":[0.00003117291,0.0004458668,0.6006382,0.0001038214,0.00004419945,0.001402968,0.3791755,0.001021442,0.001928395,0.0003397044,0.01471339,0.0001552718],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969983,0.0002461483,0.0002861482,0.0001794412,0.000007452675,0.00002597647,0.00003449446,0.00000381859,0.002218156],"genre_scores_gemma":[0.9978439,0.0001730374,0.0001539776,0.00005068171,0.000004142124,0.00002542974,0.00004325984,0.00000389114,0.001701702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3660249,"threshold_uncertainty_score":0.736361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207225610253767,"score_gpt":0.2822340948123511,"score_spread":0.2601618387098134,"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."}}