{"id":"W3113583650","doi":"10.1177/0952695120976330","title":"The past of predicting the future: A review of the multidisciplinary history of affective forecasting","year":2020,"lang":"en","type":"review","venue":"History of the Human Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multidisciplinary approach; Utilitarianism; Affect (linguistics); TRACE (psycholinguistics); Psychology; Cognition; Order (exchange); Cognitive psychology; Social psychology; Positive economics; Epistemology; Economics; Sociology; Social science; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.01329728,0.0003890669,0.00196533,0.0001976147,0.0008252496,0.00002864912,0.00844159,0.000144537,0.00007567606],"category_scores_gemma":[0.003890137,0.0001426137,0.001735703,0.001222961,0.006444939,0.0001959045,0.00169347,0.0006129781,0.000005346456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009775466,"about_ca_system_score_gemma":0.002486743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006570246,"about_ca_topic_score_gemma":0.0001130685,"domain_scores_codex":[0.9923296,0.001698128,0.002731658,0.0007225311,0.00222772,0.0002903857],"domain_scores_gemma":[0.9832782,0.005364645,0.008854123,0.001948076,0.0004917184,0.00006330341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006124171,0.00006005763,0.0001938968,0.003800622,0.00003614396,7.73958e-7,0.003174922,0.00001299346,0.0000090413,0.0003060549,0.04864897,0.9437504],"study_design_scores_gemma":[0.0000623494,0.0001218319,0.0001584287,0.02460674,0.0003888505,0.00001728079,0.001076406,0.00008609001,0.000001780107,0.001284214,0.9720319,0.0001641076],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001367054,0.9855089,0.000004344156,0.0002651514,0.005935253,0.001010446,0.00004997987,0.000009463371,0.005849464],"genre_scores_gemma":[0.003987935,0.9914944,0.0001655747,0.0000905172,0.0004182991,0.00006007549,0.000001292218,0.00003617424,0.00374575],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9435863,"threshold_uncertainty_score":0.9969232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3083834255634008,"score_gpt":0.4150042689328311,"score_spread":0.1066208433694303,"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."}}