{"id":"W1517449658","doi":"10.2139/ssrn.977508","title":"Gender, Affect and Intertemporal Consistency: An Experimental Approach","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Affect (linguistics); Consistency (knowledge bases); Mood; Patience; Intertemporal choice; Psychology; Hyperbolic discounting; Discounting; Time preference; Delay discounting; Temporal discounting; Social psychology; Economics; Econometrics; Developmental psychology; Impulsivity; Mathematics; Microeconomics","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":[0.005879895,0.001573584,0.001872733,0.0007892855,0.001117902,0.002375068,0.002214757,0.002241399,0.01875873],"category_scores_gemma":[0.02201701,0.001393115,0.0008437684,0.0008988943,0.002707077,0.001691842,0.002039421,0.002495628,0.001307059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009140805,"about_ca_system_score_gemma":0.0009375348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101354,"about_ca_topic_score_gemma":0.0009056251,"domain_scores_codex":[0.9965525,0.001209738,0.0002810059,0.0009465319,0.0007024676,0.0003078888],"domain_scores_gemma":[0.9718989,0.01976303,0.00286179,0.003684622,0.0007151983,0.001076414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.3388793,0.2561049,0.03045689,0.001278516,0.0007491334,0.0007152306,0.008191996,0.006128779,0.2731892,0.02784365,0.003159049,0.05330323],"study_design_scores_gemma":[0.103323,0.4324335,0.210433,0.0002975051,0.004884196,0.001069719,0.003231777,0.06127428,0.07949784,0.08692134,0.01580203,0.0008319322],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919264,0.00006179119,0.002416466,0.00009574696,0.0001509049,0.001153082,0.0003873633,0.00003517118,0.003773153],"genre_scores_gemma":[0.9544299,0.0002438254,0.01737813,0.0004716704,0.0003465244,0.01097109,0.0006944786,0.0001973365,0.01526705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01875873,"threshold_uncertainty_score":0.06275427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1203732355224212,"score_gpt":0.4033648141448455,"score_spread":0.2829915786224243,"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."}}