{"id":"W2586641916","doi":"10.7202/1038683ar","title":"The Need for Speed! Experimenting with “Speed Training” in the Scientific/Technical Translation Classroom","year":2017,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Educational Strategies and Epistemologies","field":"Psychology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Training (meteorology); Feeling; Situated; Mathematics education; Computer science; Medical education; Psychology; Artificial intelligence; Medicine; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.00287705,0.0001663856,0.0002336435,0.00007111899,0.002752154,0.001575127,0.0009568172,0.00007005026,0.00005382318],"category_scores_gemma":[0.0001842356,0.00008101023,0.0002068239,0.000129602,0.0008635907,0.0003092937,0.00001136217,0.000382092,0.000004901754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003424955,"about_ca_system_score_gemma":0.0001060838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005298835,"about_ca_topic_score_gemma":0.000302157,"domain_scores_codex":[0.9983636,0.0002445749,0.00038497,0.0002506385,0.0002991552,0.0004570293],"domain_scores_gemma":[0.9984462,0.0005827392,0.0003264179,0.000483489,0.0001030528,0.00005808202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002545848,0.0008742248,0.02875032,0.00007149811,0.002723117,0.0001505663,0.0632578,0.0004397164,0.01629422,0.4017044,0.01610995,0.4670784],"study_design_scores_gemma":[0.003514065,0.0009569922,0.6244445,0.00009853918,0.0009375417,0.002326858,0.06648857,0.0001366958,0.0007090943,0.115707,0.1840319,0.0006481588],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635258,0.01192117,0.001340187,0.01362067,0.001982645,0.0005414027,0.000006287626,0.00002485976,0.007036958],"genre_scores_gemma":[0.9965113,0.0001950167,0.001869791,0.00007072048,0.0003884276,0.00004304243,0.000003830276,0.00001962792,0.0008982884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5956942,"threshold_uncertainty_score":0.9994614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2131004535600362,"score_gpt":0.3958490128751163,"score_spread":0.1827485593150801,"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."}}