{"id":"W7083588089","doi":"10.5281/zenodo.17213636","title":"EMOTIONAL INTELLIGENCE IN MACHINES: CAN AI CULTIVATE EMPATHY?","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ArcelorMittal (Canada)","funders":"","keywords":"Emotional intelligence; Cognition; Field (mathematics); Context (archaeology); Novelty; Human intelligence; Affective computing; Emotional competence","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":[0.002264667,0.0004239173,0.0003740352,0.0005746164,0.001713337,0.005472775,0.0005282726,0.002264692,0.003923008],"category_scores_gemma":[0.007514001,0.0002078151,0.00040463,0.0003838673,0.008709441,0.007052336,0.002926268,0.002906945,0.0007444826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008520299,"about_ca_system_score_gemma":0.0006474458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003132331,"about_ca_topic_score_gemma":0.0001881604,"domain_scores_codex":[0.9980175,0.001315709,0.00003991431,0.0001878214,0.0002099766,0.0002290636],"domain_scores_gemma":[0.9974908,0.00175238,0.0002307511,0.0001632067,0.0001607049,0.000202241],"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":[0.0001413956,0.0001692994,0.00559346,0.0006257591,0.00007939756,0.0009516061,0.09391484,0.001031321,0.006677967,0.7303783,0.01090317,0.1495335],"study_design_scores_gemma":[0.00005110009,0.0002782503,0.01200674,0.000808149,0.00007130088,0.001673224,0.03796157,0.0048946,0.002718832,0.7970197,0.1424277,0.00008872987],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2972947,0.03160149,0.08101173,0.1409152,0.002206097,0.0001602289,0.00008558413,0.0002574943,0.4464674],"genre_scores_gemma":[0.9800842,0.004823395,0.004161053,0.004623659,0.0002696443,0.00006668261,0.00001687846,0.00002512639,0.005929398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005472775,"threshold_uncertainty_score":0.01312375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188278874810345,"score_gpt":0.2525820637869173,"score_spread":0.2306992750388139,"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."}}