{"id":"W7098628077","doi":"","title":"An English &amp;quot;like no other&amp;quot;? Language contact and change in Québec. New Ways of Analyzing Variation 31","year":2002,"lang":"en","type":"article","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feeling; Variation (astronomy); Language contact; Work (physics); Language change","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":[0.002803806,0.0003183636,0.0005077454,0.00253508,0.006215051,0.006031238,0.001574944,0.001417265,0.01143613],"category_scores_gemma":[0.007159296,0.0002169092,0.0003620376,0.009081226,0.005778372,0.004896253,0.001485594,0.001201168,0.0004358125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05054055,"about_ca_system_score_gemma":0.02392766,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9893312,"about_ca_topic_score_gemma":0.9946463,"domain_scores_codex":[0.9976934,0.0009180962,0.00006646779,0.0003523428,0.0004859626,0.0004837694],"domain_scores_gemma":[0.9963881,0.001216206,0.0003922674,0.0003067537,0.001260588,0.000436092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001639163,0.00007955811,0.1824715,0.0005176219,0.0001949727,0.001067194,0.1678091,0.001364976,0.0008379472,0.2063256,0.1311671,0.3080004],"study_design_scores_gemma":[0.00001564525,0.00004685871,0.483175,0.0009252466,0.00008917043,0.0002554587,0.1412102,0.002958271,0.0004078519,0.0250497,0.3456992,0.0001673008],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4468602,0.08610097,0.01998241,0.1689315,0.00160203,0.0002095778,0.0129844,0.0003649661,0.262964],"genre_scores_gemma":[0.9574725,0.004756364,0.003318442,0.002316268,0.0000882361,0.00007704909,0.0007266855,0.00007730803,0.03116724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05054055,"threshold_uncertainty_score":0.3666991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09122105800133294,"score_gpt":0.2298607137958396,"score_spread":0.1386396557945066,"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."}}