{"id":"W4256573060","doi":"10.1017/cnj.2016.1","title":"De la variation lexicale en franco-ontarien: les données du corpus de Casselman (Ontario)","year":2016,"lang":"fr","type":"article","venue":"The Canadian Journal of Linguistics / La revue canadienne de linguistique","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Humanities; Philosophy; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001204024,0.0003333954,0.0003822859,0.003994142,0.004001306,0.002012965,0.0005760215,0.0003587789,0.006350974],"category_scores_gemma":[0.004252539,0.0002817237,0.0002255641,0.01045423,0.002326811,0.0005599161,0.001278333,0.000337852,0.000578267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01380533,"about_ca_system_score_gemma":0.01336138,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.946317,"about_ca_topic_score_gemma":0.9830566,"domain_scores_codex":[0.9988928,0.0001665591,0.0001091159,0.0003058066,0.0003392423,0.0001864695],"domain_scores_gemma":[0.9960636,0.00163746,0.0004253161,0.0003908536,0.001337555,0.0001450562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004172076,0.00005324303,0.413866,0.001912373,0.0001866224,0.002436991,0.3639022,0.0009285712,0.02444268,0.01427225,0.01997161,0.1576103],"study_design_scores_gemma":[0.00001096886,0.00001589684,0.8576363,0.0001938457,0.00005989526,0.0004098309,0.03562354,0.0001938672,0.00206205,0.0003987536,0.1033559,0.00003910304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9375579,0.00320821,0.002348631,0.0004855316,0.00003516203,0.0001255802,0.01776623,0.00003760038,0.03843505],"genre_scores_gemma":[0.9688219,0.001509113,0.003099486,0.0001229256,0.00001503,0.0002127402,0.01023472,0.00006922007,0.01591499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05368304,"threshold_uncertainty_score":0.1079983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583133438107769,"score_gpt":0.2506497324387065,"score_spread":0.2348183980576288,"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."}}