{"id":"W7125585764","doi":"10.1109/cascon66301.2025.00090","title":"Kantian-Utilitarian XAI: Meta-Explained","year":2025,"lang":"","type":"article","venue":"","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Regret; Artifact (error); Session (web analytics); Certification; Code (set theory); TRACE (psycholinguistics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002847698,0.00180301,0.0005397319,0.001111757,0.0007120394,0.00332968,0.003515477,0.001800425,0.05685431],"category_scores_gemma":[0.008522174,0.001257537,0.002258709,0.00077273,0.0009984799,0.0044612,0.005457613,0.003365981,0.0144226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001502401,"about_ca_system_score_gemma":0.001516821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002969159,"about_ca_topic_score_gemma":0.00467456,"domain_scores_codex":[0.9984944,0.0005004956,0.0001139383,0.0003187363,0.0004129694,0.0001595644],"domain_scores_gemma":[0.9979436,0.0009640871,0.00008273777,0.0007090709,0.000212894,0.00008763705],"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":[0.0008904404,0.0004769537,0.00385079,0.001500026,0.0003713025,0.0006518137,0.00312547,0.08699989,0.01045854,0.3925048,0.1457339,0.3534361],"study_design_scores_gemma":[0.000156075,0.00008720159,0.0007143009,0.0003494886,0.0001247392,0.0002949051,0.0001546436,0.4389555,0.01510065,0.2219139,0.3220209,0.0001277704],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003152792,0.0001592059,0.8855854,0.0006710912,0.00009525402,0.0002274138,0.002686132,0.09347677,0.01394595],"genre_scores_gemma":[0.09088662,0.0003989452,0.8514977,0.0007527439,0.00006734981,0.001027438,0.01034952,0.02006885,0.02495098],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05685431,"threshold_uncertainty_score":0.1901966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06326643969978005,"score_gpt":0.312312165394461,"score_spread":0.2490457256946809,"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."}}