{"id":"W2942801696","doi":"10.3968/10952","title":"The Influence of Emotion on Inter-Temporal Choice: Based on Evaluation Tendency Framework Theory","year":2019,"lang":"en","type":"article","venue":"Canadian social science","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Connotation; Cognitive psychology; Perception; Valence (chemistry); Psychology; Emotional valence; Cognition; Neurocognitive; Emotion classification; Computer science; Cognitive science; Neuroscience","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002462422,0.0002296113,0.0003624413,0.0007468431,0.0004414243,0.002584785,0.0004486345,0.0005615695,0.003520122],"category_scores_gemma":[0.007829204,0.0001406021,0.000838839,0.0006366664,0.00142003,0.001751212,0.000898202,0.0008359135,0.0002001623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154624,"about_ca_system_score_gemma":0.0005365064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001492509,"about_ca_topic_score_gemma":0.0008850056,"domain_scores_codex":[0.9985387,0.0007504718,0.00005995864,0.0002076153,0.0002832261,0.0001600232],"domain_scores_gemma":[0.9943087,0.004066551,0.0005669609,0.0002456754,0.0005576584,0.0002544718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005150946,0.0003242826,0.04107004,0.0002422393,0.0002110915,0.000387798,0.004172897,0.01391633,0.006084922,0.8621113,0.001367376,0.0695968],"study_design_scores_gemma":[0.0001006611,0.0003848556,0.101218,0.0001228259,0.0002428984,0.0003412223,0.002669854,0.1409293,0.002468003,0.7453728,0.006017328,0.0001322161],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6861597,0.001281407,0.1862911,0.00288822,0.0001289586,0.0001371679,0.0001087656,0.00005193392,0.1229527],"genre_scores_gemma":[0.99291,0.0002593518,0.005450476,0.00005530978,0.00002324161,0.0000363915,0.00001466374,0.000008788873,0.001241894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003520122,"threshold_uncertainty_score":0.01302266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06238830382550849,"score_gpt":0.3819275131960503,"score_spread":0.3195392093705418,"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."}}