{"id":"W2031390459","doi":"10.3138/cmlr.60.3.409","title":"Intensive French and Intensive English: Similarities and Differences","year":2004,"lang":"en","type":"article","venue":"Canadian Modern Language Review/ La Revue canadienne des langues vivantes","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fluency; Curriculum; Selection (genetic algorithm); AP French Language; Reading (process); Mathematics education; Relation (database); Psychology; Pedagogy; Computer science; Linguistics; Artificial intelligence; Language assessment","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0009113581,0.0002609648,0.0002862806,0.004003812,0.00240643,0.002913083,0.0006226096,0.0004753271,0.004616802],"category_scores_gemma":[0.002301735,0.0001571067,0.0001941521,0.005496636,0.002469333,0.0008697527,0.001135987,0.000801661,0.00039274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0126527,"about_ca_system_score_gemma":0.0170273,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5081028,"about_ca_topic_score_gemma":0.6504638,"domain_scores_codex":[0.998569,0.0001698385,0.00005567836,0.0001520555,0.0004362118,0.0006172479],"domain_scores_gemma":[0.9984465,0.0003286292,0.0002322925,0.00005057998,0.0004692971,0.000472641],"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":[0.0003293917,0.0002684881,0.07285143,0.001507133,0.00004199881,0.003150005,0.08661458,0.0004689505,0.002712751,0.107883,0.01570688,0.7084655],"study_design_scores_gemma":[0.00001673472,0.0002286945,0.382686,0.001154792,0.00003457182,0.003560655,0.03231936,0.0001410331,0.0007318684,0.003512319,0.5755681,0.00004582395],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.455604,0.1149721,0.003453613,0.007264932,0.0006527401,0.0002475946,0.0009833775,0.0002114592,0.4166102],"genre_scores_gemma":[0.9141748,0.04496837,0.00182007,0.001318064,0.0002142448,0.0001128161,0.0005928478,0.000106183,0.03669266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5081028,"threshold_uncertainty_score":0.9895882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794575817490972,"score_gpt":0.2055373230730714,"score_spread":0.1875915648981617,"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."}}