{"id":"W2947802037","doi":"10.5539/elt.v12n6p217","title":"Socially-shared Metacognitive Regulation Episodes Between Undergraduate Engineering Students During a Collaborative Genre Analysis Task in an English for Academic Purposes Course","year":2019,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metacognition; Psychology; Task (project management); Task analysis; English for academic purposes; Collaborative learning; Discourse analysis; Computer-mediated communication; Mathematics education; Collaborative writing; Pedagogy; Linguistics; Cognition; The Internet; World Wide Web; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005318306,0.0004362067,0.0008584597,0.0008802884,0.0002937379,0.0001896438,0.0005151688,0.0003344763,0.0001062234],"category_scores_gemma":[0.002565782,0.0004701447,0.0002114689,0.001294938,0.00004289717,0.0007172158,0.0001065383,0.002011012,0.0000121467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002817129,"about_ca_system_score_gemma":0.0000671402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001451141,"about_ca_topic_score_gemma":0.00007860758,"domain_scores_codex":[0.9945313,0.002736957,0.0006932651,0.0008680034,0.0004557004,0.0007147635],"domain_scores_gemma":[0.99731,0.001334225,0.000464017,0.0004383591,0.0003358577,0.0001175795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001321684,0.0001478167,0.4190179,0.00005601988,0.001715673,0.00001859565,0.566484,0.00295907,0.005031012,0.00126533,0.00002146401,0.00315094],"study_design_scores_gemma":[0.003462837,0.0002140216,0.81782,0.0001774374,0.001032774,0.000001001049,0.1743691,0.001141548,0.0006009516,0.0001337247,0.0001854921,0.0008611684],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863116,0.0003144846,0.00992859,0.00004323543,0.0006238596,0.001101114,0.0001895625,0.0004846802,0.00100287],"genre_scores_gemma":[0.9892472,0.000002018162,0.007547549,0.00004790285,0.001110704,0.0001902141,0.0007017365,0.0001084969,0.0010442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3988021,"threshold_uncertainty_score":0.9997751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687113671096911,"score_gpt":0.3818200577437394,"score_spread":0.3649489210327703,"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."}}