{"id":"W1981262337","doi":"10.1007/s00355-006-0188-x","title":"Variable-population extensions of social aggregation theorems","year":2006,"lang":"en","type":"article","venue":"Social Choice and Welfare","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Variable (mathematics); Extension (predicate logic); Population; Utilitarianism; Social choice theory; Mathematical economics; Contrast (vision); Econometrics; Economics; Social policy; Public finance; Ex-ante; Random variable; Mathematics; Computer science; Statistics; Sociology; Political science; Demography; Artificial intelligence; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0007720239,0.0001084486,0.0002698309,0.0001292674,0.0008012204,0.0001443529,0.0001863975,0.0001604932,0.0002824438],"category_scores_gemma":[0.0003857551,0.00008939208,0.0001044312,0.0004081654,0.0001037969,0.0002771819,0.00006515686,0.00009754002,0.00001870711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003053476,"about_ca_system_score_gemma":0.00002112723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008911662,"about_ca_topic_score_gemma":0.0001977649,"domain_scores_codex":[0.9984728,0.00009592146,0.0005277115,0.0002911416,0.0004545806,0.0001579071],"domain_scores_gemma":[0.9989326,0.0002945732,0.0003391483,0.0001401695,0.000261887,0.00003160247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003185077,0.0001271473,0.05951379,0.000006850423,0.000009362599,0.000001503405,0.0006998561,0.00006769986,0.000424955,0.3147822,0.0058621,0.6184727],"study_design_scores_gemma":[0.0002801345,0.00002048224,0.5006022,0.000007220319,0.00002412976,0.000001398853,0.0007360927,0.0001328907,0.00002134832,0.4732308,0.02481431,0.0001289218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910801,0.00004259664,0.0003595689,0.001542388,0.0002966073,0.00009333769,0.00005874922,0.00002947607,0.006497194],"genre_scores_gemma":[0.9988046,0.000001360753,0.0003192404,0.00006302768,0.0004558504,0.000003733173,0.00003958675,0.000009859175,0.0003027456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6183438,"threshold_uncertainty_score":0.6162421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04997353019053637,"score_gpt":0.3574628823402215,"score_spread":0.3074893521496851,"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."}}