{"id":"W7115728273","doi":"10.1016/j.amper.2025.100252","title":"Use of English in engineering workplace: Frequency, skill hierarchy, and functions","year":2025,"lang":"en","type":"article","venue":"Ampersand","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Variety (cybernetics); Work (physics)","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":[0.002624144,0.0001645469,0.0002360784,0.001790466,0.000922037,0.002136156,0.0003852219,0.000325754,0.001380009],"category_scores_gemma":[0.01217239,0.0001622657,0.0001119428,0.000980863,0.001135028,0.001124196,0.001789949,0.0003947848,0.0003045015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006045685,"about_ca_system_score_gemma":0.0007519231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003409159,"about_ca_topic_score_gemma":0.00678593,"domain_scores_codex":[0.997615,0.001009592,0.0002678275,0.0001894563,0.0005990183,0.000319122],"domain_scores_gemma":[0.986762,0.008034384,0.002566465,0.0003299363,0.001578909,0.0007282625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001446013,0.0001851279,0.5244285,0.0003052402,0.000023894,0.0009041827,0.3842085,0.0001008016,0.005911842,0.0004792978,0.0003867724,0.08292124],"study_design_scores_gemma":[0.00000449717,0.0001748762,0.6657753,0.0002045934,0.00001259835,0.0008214129,0.3279826,0.0002234294,0.000778869,0.0003141752,0.00367228,0.00003534678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979396,0.0002333282,0.0002197378,0.00007857764,0.00000359259,0.000005019469,0.00001500257,0.000002681112,0.001502385],"genre_scores_gemma":[0.9990127,0.0002559553,0.0002008011,0.0000315695,0.000004795626,0.000008511388,0.00001922512,0.000003272114,0.0004631887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003409159,"threshold_uncertainty_score":0.01387793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673993338570044,"score_gpt":0.2135262490364781,"score_spread":0.1967863156507776,"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."}}