{"id":"W4379527561","doi":"10.26634/jelt.13.2.19343","title":"It's a long story, but DDL is worth it. Data-driven learning as multimodel method for english sessions in turkish prep-classes","year":2023,"lang":"en","type":"article","venue":"i-manager’s Journal on English Language Teaching","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Turkish; Computer science; Mathematics education; Language acquisition; Class (philosophy); Literacy; Focus (optics); Psychology; Natural language processing; Artificial intelligence; Linguistics; Pedagogy","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":[0.01282216,0.0009040057,0.0006482191,0.001579258,0.004829481,0.009093756,0.002634237,0.004465848,0.02022421],"category_scores_gemma":[0.04568636,0.0004046113,0.001015636,0.001354434,0.008880093,0.02141789,0.007606338,0.01121775,0.009565871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004390462,"about_ca_system_score_gemma":0.003228598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00648755,"about_ca_topic_score_gemma":0.008300672,"domain_scores_codex":[0.9890098,0.005903819,0.0004695018,0.001125808,0.0027981,0.0006930365],"domain_scores_gemma":[0.9735835,0.01197475,0.001062054,0.002837511,0.006381336,0.004160822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000217123,0.0002105385,0.00334133,0.001012867,0.00006134991,0.0005935849,0.01348742,0.0004149174,0.001573633,0.05122412,0.6652818,0.2625814],"study_design_scores_gemma":[0.00002259548,0.0001575207,0.001391214,0.0007135187,0.00001910882,0.0006023172,0.01055053,0.000516544,0.0006966532,0.01378577,0.9714569,0.00008730699],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01073408,0.01820423,0.05365357,0.7951961,0.05033921,0.0003860948,0.000766494,0.002283118,0.06843706],"genre_scores_gemma":[0.2278387,0.02035636,0.1572455,0.3459293,0.02307214,0.001696538,0.001685623,0.00534134,0.2168345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02022421,"threshold_uncertainty_score":0.06781083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04310849094468342,"score_gpt":0.3995961321212456,"score_spread":0.3564876411765621,"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."}}