{"id":"W4388333366","doi":"10.3390/educsci13111109","title":"Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice","year":2023,"lang":"en","type":"article","venue":"Education Sciences","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":350,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Transformative learning; Generative grammar; Engineering ethics; Competence (human resources); Equity (law); Higher education; Psychology; Sociology; Computer science; Pedagogy; Artificial intelligence; Political science; Social psychology; Engineering","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":[0.0006384578,0.0001047659,0.0001238813,0.0003374715,0.0009253653,0.0001763819,0.00006551288,0.00007550611,0.0002108707],"category_scores_gemma":[0.002090696,0.00009698413,0.00003713028,0.001002708,0.0002919572,0.0004389091,0.0000166982,0.00009309279,0.0001421587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008399932,"about_ca_system_score_gemma":0.003969872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001857858,"about_ca_topic_score_gemma":0.00003042068,"domain_scores_codex":[0.9987267,0.00006236465,0.0004041895,0.00039182,0.0001885496,0.0002264049],"domain_scores_gemma":[0.9973918,0.001216508,0.0001446979,0.0001957247,0.0008878527,0.0001634639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001629977,0.0003955888,0.002010954,0.00004366946,0.00001249872,1.117369e-7,0.003527235,0.00003605093,0.001516987,0.6831539,0.03390919,0.2753775],"study_design_scores_gemma":[0.00001844246,0.0003418803,0.0149433,0.00009670614,0.00009567864,0.00006053604,0.04015457,0.0008993134,0.008988136,0.8771869,0.05696031,0.00025424],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2225275,0.001318672,0.004355731,0.7470683,0.006357884,0.002698155,0.00002298857,0.0002741328,0.01537667],"genre_scores_gemma":[0.961702,0.0002318266,0.02671343,0.005993087,0.001207204,0.001017038,0.00007847459,0.00001202884,0.003044843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7410752,"threshold_uncertainty_score":0.7117255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5330349575694349,"score_gpt":0.5737615564612487,"score_spread":0.04072659889181385,"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."}}