{"id":"W1978242712","doi":"10.3138/cmlr.59.3.393","title":"Analyzing Late Interlanguage with Learner Corpora: Québec Replications of Three European Studies","year":2003,"lang":"en","type":"article","venue":"Canadian Modern Language Review/ La Revue canadienne des langues vivantes","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interlanguage; Context (archaeology); Second-language acquisition; Computer science; Literacy; Linguistics; Character (mathematics); Psychology; Mathematics education; Pedagogy; History; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01603462,0.0007992735,0.001148265,0.007009538,0.008620542,0.003549246,0.002816309,0.001502367,0.00364825],"category_scores_gemma":[0.03639655,0.0004310561,0.0005039998,0.01413604,0.003458169,0.002051216,0.003788205,0.001312944,0.0007160914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02581329,"about_ca_system_score_gemma":0.02006073,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.905722,"about_ca_topic_score_gemma":0.9668782,"domain_scores_codex":[0.9898368,0.0044471,0.0007084524,0.001370289,0.002659853,0.0009775255],"domain_scores_gemma":[0.9408647,0.01733231,0.003818958,0.006253974,0.02947482,0.002255215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.001059511,0.002028615,0.352198,0.000764196,0.0004793965,0.002881622,0.4975499,0.0006993719,0.00425399,0.003705726,0.01527709,0.1191025],"study_design_scores_gemma":[0.0001492782,0.0004582917,0.7899881,0.0005077674,0.0001939931,0.000652013,0.1437912,0.0009932941,0.002448657,0.0004144241,0.06026736,0.0001356117],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874569,0.001176643,0.0007354104,0.0004959466,0.00003163605,0.0003665711,0.002512685,0.00004736247,0.007176946],"genre_scores_gemma":[0.9837356,0.0009135447,0.00227982,0.0005714233,0.00002684914,0.0007785793,0.004379728,0.0001024258,0.007212066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.905722,"threshold_uncertainty_score":0.1896663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02980851529886725,"score_gpt":0.2806767301598688,"score_spread":0.2508682148610016,"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."}}