{"id":"W2763702331","doi":"10.1002/tesj.340","title":"Preparing Diverse Learners for University: A Strategy for Teaching <scp>EAP</scp> Students","year":2017,"lang":"en","type":"article","venue":"TESOL Journal","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Mathematics education; Context (archaeology); Population; Point (geometry); Heuristics; Psychology; Pedagogy; Computer science; Sociology","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":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008294409,0.0001420453,0.0001849304,0.000113482,0.005045175,0.001543816,0.0006088158,0.00004826308,0.0001146877],"category_scores_gemma":[0.0005666094,0.000130842,0.0001891115,0.00000486311,0.0001100073,0.0006049872,0.0001037085,0.000527536,0.00001272477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006465659,"about_ca_system_score_gemma":0.00004483344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003601697,"about_ca_topic_score_gemma":0.0004580735,"domain_scores_codex":[0.9990467,0.00006572238,0.0001565475,0.0001886759,0.0001793059,0.0003630874],"domain_scores_gemma":[0.9989989,0.0002663414,0.0003366915,0.0002082685,0.00007263984,0.0001171852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000225971,0.0005233087,0.02269746,0.0002461847,0.001562352,0.0002238912,0.4213096,0.001354136,0.0004196873,0.1191181,0.0945135,0.3378058],"study_design_scores_gemma":[0.003243073,0.000427306,0.0009237619,0.0001504269,0.000204098,0.00005199671,0.2698304,0.001458472,0.00001918545,0.0008832728,0.7226368,0.0001712048],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9248968,0.000109243,0.001329849,0.00007263,0.0006305091,0.000245868,0.00002649135,0.00007587141,0.07261278],"genre_scores_gemma":[0.9425216,0.000006482873,0.0005191275,0.00009480119,0.001394266,0.000002541795,0.000007332337,0.00002552696,0.05542834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6281233,"threshold_uncertainty_score":0.9994927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595427843572156,"score_gpt":0.3084319527570193,"score_spread":0.2524776743212978,"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."}}