{"id":"W4387333105","doi":"10.1075/task.22013.wou","title":"Modelling plurilingual instruction through a crosslinguistic-communicative task sequence","year":2023,"lang":"en","type":"article","venue":"TASK Journal on Task-Based Language Teaching and Learning","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"","keywords":"Task (project management); Computer science; Field (mathematics); Process (computing); Task analysis; Test (biology); Perception; Linguistics; Sequence (biology); Psychology; Natural language processing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004148469,0.0004506242,0.0004761526,0.0004438545,0.006556624,0.001083836,0.0004065433,0.0001382023,0.0002293013],"category_scores_gemma":[0.001984107,0.0003980697,0.0002064357,0.0001444737,0.0003399844,0.0003950596,0.00009451186,0.007239929,0.0001364489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001286593,"about_ca_system_score_gemma":0.0001230515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001410603,"about_ca_topic_score_gemma":0.00005042821,"domain_scores_codex":[0.9955082,0.002051118,0.0006269907,0.000520299,0.0005630151,0.000730399],"domain_scores_gemma":[0.9974489,0.001280486,0.0005570553,0.0003829475,0.0001252889,0.0002053627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001886659,0.0001005974,0.0003172497,0.00009525893,0.0001290399,0.0003602324,0.5727394,0.3690134,0.0008969429,0.01151003,0.0003705902,0.04427855],"study_design_scores_gemma":[0.003382078,0.001228767,0.00004174826,0.002045506,0.0001848423,0.0003195666,0.3092211,0.3589788,0.0001141727,0.001584198,0.3213229,0.001576328],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762903,0.0008341299,0.005856857,0.0004650365,0.000664725,0.0001423001,0.0000241278,0.000918566,0.01480393],"genre_scores_gemma":[0.9911622,0.00007400646,0.002811871,0.0006205642,0.001757907,0.00000961672,0.0001063739,0.0001051495,0.003352265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3209523,"threshold_uncertainty_score":0.9999532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0502108474219241,"score_gpt":0.3111208159656612,"score_spread":0.260909968543737,"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."}}