{"id":"W4412870784","doi":"10.24908/pceea.2025.19678","title":"Artificial Intelligence (AI), Sustainability and Engineering Education: Implementation trends in STEM to realize Society 5.0.","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Sustainability in Higher Education","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Polytechnique Montréal","keywords":"Sustainability; Engineering ethics; Engineering management; Engineering; Computer science; Political science; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001644549,0.0001557749,0.0001779104,0.0006866286,0.0003262468,0.000222484,0.0003172426,0.0001863176,0.00002855212],"category_scores_gemma":[0.001760654,0.0001854658,0.00007918553,0.002617994,0.00004107112,0.0003888333,0.00004232072,0.0002421938,0.000001067095],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0135802,"about_ca_system_score_gemma":0.005058375,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08125845,"about_ca_topic_score_gemma":0.07226215,"domain_scores_codex":[0.9983877,0.00003011257,0.0004773674,0.0003215346,0.0003451808,0.0004381212],"domain_scores_gemma":[0.9979039,0.0001309008,0.000198367,0.0001390861,0.00140353,0.00022416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000657347,0.0001975796,0.4593903,0.0005971775,0.00005808968,2.834475e-8,0.06314468,0.001422043,0.0001902541,0.3789965,0.01876112,0.07723574],"study_design_scores_gemma":[0.00009053181,0.00002327997,0.7665977,0.000215598,0.00006890863,4.914317e-7,0.1433725,0.0008648452,0.001024471,0.01192464,0.07534336,0.000473635],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8941869,0.0001085776,0.00009141771,0.1003127,0.002302321,0.001183104,0.0000118477,0.00009014978,0.001713028],"genre_scores_gemma":[0.9963806,0.000009387004,0.0006377968,0.0005161061,0.0001927016,0.0002785543,0.000008167043,0.00001536966,0.001961368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670718,"threshold_uncertainty_score":0.9902065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009869537637383591,"score_gpt":0.3252709773836961,"score_spread":0.3154014397463125,"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."}}