{"id":"W4417018336","doi":"10.63721/25jpair0114","title":"Quantifying the Emotional Value of Goods and Services: Values of Hate and Love and Everything in between","year":2025,"lang":"","type":"article","venue":"Journal of Pioneering Artificial Intelligence Research","topic":"Emotions and Moral Behavior","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for International Peace and Security","funders":"","keywords":"Value (mathematics); Blueprint; Identity (music); Corporate governance; Goods and services; Affect (linguistics); Index (typography); Component (thermodynamics); Term (time)","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":[0.002420336,0.0004622622,0.000358431,0.00120653,0.0006676122,0.004815512,0.0004313785,0.0009996473,0.002761294],"category_scores_gemma":[0.01540576,0.0002477619,0.0004590384,0.001185799,0.004489435,0.007128722,0.00252758,0.001341986,0.0002614654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001179201,"about_ca_system_score_gemma":0.0003716119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008340222,"about_ca_topic_score_gemma":0.0007260899,"domain_scores_codex":[0.998524,0.0007165828,0.00006957125,0.0001767071,0.0004124219,0.0001007637],"domain_scores_gemma":[0.9953346,0.002475551,0.0007626149,0.00063268,0.0005033055,0.0002912978],"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":[0.0005538095,0.0001958454,0.07682545,0.0006728409,0.0003657144,0.0002353961,0.008884848,0.01027084,0.008794121,0.6687428,0.005402211,0.2190561],"study_design_scores_gemma":[0.00002856531,0.000301895,0.1071047,0.0005435707,0.0001857043,0.0004716691,0.008450653,0.02796015,0.00472855,0.8232505,0.02677667,0.0001974737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6742926,0.004175365,0.1988808,0.01073286,0.0004824724,0.0001037503,0.000731628,0.000131314,0.1104693],"genre_scores_gemma":[0.9886014,0.0004661952,0.009130676,0.0003117277,0.00008850092,0.00003618193,0.00008380089,0.00002270586,0.001258785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004815512,"threshold_uncertainty_score":0.0128001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2422444235119766,"score_gpt":0.4883903458105792,"score_spread":0.2461459222986026,"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."}}