{"id":"W2374008605","doi":"10.21083/nrsc.v0i9.3677","title":"Outwit, Outlast, Outplay: Survival Techniques (for Teachers and Students) in the Large Language Classroom","year":2016,"lang":"en","type":"article","venue":"Nouvelle Revue Synergies Canada","topic":"EFL/ESL Teaching and Learning","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Class size; Mathematics education; Class (philosophy); Affect (linguistics); Norm (philosophy); Psychology; Pedagogy; Computer science; Communication; Political science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007982522,0.0001776264,0.0002342633,0.00006605969,0.0003548836,0.0001332637,0.000339306,0.00005310265,0.0001289818],"category_scores_gemma":[0.0001731176,0.0001060037,0.0000500546,0.00002926365,0.00008510552,0.00009804137,0.00007089946,0.000233193,0.000003407126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001232412,"about_ca_system_score_gemma":0.0001350794,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2449586,"about_ca_topic_score_gemma":0.9179284,"domain_scores_codex":[0.9987378,0.0001672904,0.0002290904,0.0002528046,0.0002430276,0.0003699621],"domain_scores_gemma":[0.9991233,0.0004605298,0.00008622998,0.0002487609,0.00003064467,0.00005050553],"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":[0.0001066164,0.0002778712,0.06733003,0.0003526979,0.0002480008,0.0001683813,0.6162366,0.00001163889,0.0005748226,0.09178386,0.129501,0.09340842],"study_design_scores_gemma":[0.0004374513,0.00005707467,0.00106355,0.0001258405,0.00001803907,0.000003299545,0.1431679,0.00001219204,0.00003372645,0.00006057485,0.8548015,0.0002188611],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702945,0.0005890821,0.0001497498,0.004984111,0.0007008564,0.0004746449,0.0002093023,0.0001398627,0.02245787],"genre_scores_gemma":[0.9628429,0.00003557793,0.0000779711,0.0003865467,0.0005204048,0.00006149251,0.00001251642,0.00003073332,0.03603189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7253004,"threshold_uncertainty_score":0.7600693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01363173096547067,"score_gpt":0.2425538430568058,"score_spread":0.2289221120913351,"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."}}