{"id":"W4404743848","doi":"10.1080/10963758.2024.2428613","title":"Transforming HTM Education: ChatGPT as a Catalyst for DEIB","year":2024,"lang":"en","type":"article","venue":"Journal of Hospitality & Tourism Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Catalysis; Political science; Business; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0008160077,0.0001603384,0.0003074835,0.0003688702,0.0001445105,0.0001173383,0.0001248378,0.0001476607,0.0001158467],"category_scores_gemma":[0.0004288561,0.0001407312,0.0003053059,0.0003615493,0.00005005209,0.0005910276,0.000006048006,0.0003245934,0.00004664378],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004860208,"about_ca_system_score_gemma":0.008088239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005572526,"about_ca_topic_score_gemma":0.00001556144,"domain_scores_codex":[0.998234,0.00003662319,0.0009268204,0.0002228748,0.0003381671,0.0002415701],"domain_scores_gemma":[0.9980264,0.0001649632,0.0002588347,0.0002316608,0.001029005,0.0002890979],"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":[0.0001748843,0.001666917,0.002349816,0.001310312,0.0001503262,0.000009467612,0.01572005,0.000003670707,0.001353391,0.005937447,0.06457892,0.9067448],"study_design_scores_gemma":[0.000316901,0.004815703,0.01179944,0.00545967,0.00170728,0.002813494,0.0808963,0.0002611803,0.08354332,0.1084062,0.6991366,0.0008438678],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403856,0.00948629,0.002533424,0.0345618,0.009786417,0.0008600085,0.000004953952,0.00003721616,0.0023443],"genre_scores_gemma":[0.9873283,0.0004693452,0.002091452,0.0009483492,0.006364531,0.0001005775,0.00005758687,0.00003204323,0.002607818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.905901,"threshold_uncertainty_score":0.997535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05366524291388974,"score_gpt":0.4292942541453807,"score_spread":0.375629011231491,"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."}}