{"id":"W4387408023","doi":"10.1177/13505076231201445","title":"Generative artificial intelligence and academia: Implication for research, teaching and service","year":2023,"lang":"en","type":"article","venue":"Management Learning","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Generative grammar; Artificial intelligence; Perspective (graphical); Service (business); Computer science; Service-learning; Generative model; Psychology; Pedagogy; Business","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"],"consensus_categories":[],"category_scores_codex":[0.0029768,0.0001456435,0.0001304435,0.0004835854,0.001357859,0.0005705818,0.000236511,0.000109596,0.00002602884],"category_scores_gemma":[0.0004317471,0.0001423439,0.0000191414,0.0009009421,0.00007366443,0.0008487385,0.0007611568,0.0008414971,0.0002078513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933573,"about_ca_system_score_gemma":0.000004261979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001483802,"about_ca_topic_score_gemma":0.00002989566,"domain_scores_codex":[0.9985602,0.00005002582,0.0002350173,0.0004879297,0.0002593161,0.0004074462],"domain_scores_gemma":[0.999331,0.0002332938,0.00009966252,0.0001618202,0.0001573699,0.00001687734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003951542,0.00002111915,0.0009227762,0.0007250845,0.00003200928,0.000003959942,0.000419038,0.001395341,0.001060823,0.4339083,0.003933363,0.5575387],"study_design_scores_gemma":[0.0001663366,0.00003192603,0.01071148,0.0002206621,0.00008507395,0.00000239053,0.0104521,0.2742839,0.0003839041,0.114763,0.5883635,0.0005357458],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6184586,0.0004923497,0.2549828,0.08458667,0.0008321189,0.003891096,0.00001294263,0.001607364,0.03513602],"genre_scores_gemma":[0.9939064,0.0002061135,0.001946469,0.001243243,0.0009209026,0.0002181982,0.0001470197,0.00003984668,0.001371857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5844301,"threshold_uncertainty_score":0.9999422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2527284400486348,"score_gpt":0.4068192701070737,"score_spread":0.154090830058439,"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."}}