{"id":"W2808054567","doi":"10.1002/tesj.386","title":"Selecting and adapting tasks for mixed‐level English as a second language classes","year":2018,"lang":"en","type":"article","venue":"TESOL Journal","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Task (project management); Language education; Computer science; Selection (genetic algorithm); Mathematics education; Process (computing); Teaching method; Task analysis; Language assessment; Face (sociological concept); Language proficiency; Psychology; Linguistics; Artificial intelligence; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00491327,0.0009483795,0.0004869421,0.001451725,0.001311557,0.003288222,0.002652569,0.0009089906,0.003405225],"category_scores_gemma":[0.01704819,0.0004785346,0.0006870093,0.0005182239,0.0006139793,0.002198441,0.002950805,0.001023102,0.002369247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001006607,"about_ca_system_score_gemma":0.002039869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009692776,"about_ca_topic_score_gemma":0.002529387,"domain_scores_codex":[0.9973572,0.00132012,0.0002590018,0.0003031256,0.0004450872,0.0003154702],"domain_scores_gemma":[0.9918627,0.004209773,0.0005305203,0.000945486,0.001246752,0.001204871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009471228,0.004604418,0.0290317,0.001631177,0.00004462768,0.001210518,0.0660708,0.008961558,0.06851309,0.009386466,0.01176154,0.7978371],"study_design_scores_gemma":[0.001063223,0.006336822,0.1231018,0.002307688,0.0003406233,0.002889732,0.1095026,0.07600214,0.1375077,0.03508734,0.5045569,0.001303402],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6595452,0.0002099567,0.3153839,0.0006155028,0.0001458898,0.003467444,0.0002891079,0.002717447,0.01762555],"genre_scores_gemma":[0.4449261,0.0002174512,0.5451049,0.0001418396,0.00001783501,0.002228939,0.0004751112,0.0004544425,0.006433281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00491327,"threshold_uncertainty_score":0.02598417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04977715790111208,"score_gpt":0.2863979077288328,"score_spread":0.2366207498277207,"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."}}