{"id":"W4411945991","doi":"10.1145/3736252.3742539","title":"Optimal In-Kind Redistribution","year":2025,"lang":"en","type":"article","venue":"","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Redistribution (election); Computer science; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0002963693,0.00003046922,0.00004734171,0.00008535321,0.0001243316,0.0000352234,0.00009938402,0.00004843811,0.0002623104],"category_scores_gemma":[0.00003763983,0.00002693,0.00002165468,0.0005119803,0.00008615934,0.00006896051,0.00001634911,0.00004934876,0.000008498188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002024731,"about_ca_system_score_gemma":0.00008435048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133858,"about_ca_topic_score_gemma":0.009780607,"domain_scores_codex":[0.9995422,0.00004796932,0.00007605347,0.00009918385,0.00009509959,0.0001394632],"domain_scores_gemma":[0.9998658,0.00002965987,0.00001041536,0.00005116786,0.00001878012,0.00002415705],"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":[0.00000486398,0.00003209485,0.04980005,0.00000191162,0.000005628223,0.000001280923,0.001778845,0.000004931042,0.000008113256,0.8938416,0.007583366,0.04693731],"study_design_scores_gemma":[0.0004297403,0.00002256204,0.472222,0.00002723347,0.000009192108,1.325931e-7,0.01542666,0.0001017173,0.0001386143,0.07036614,0.44109,0.0001659618],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1259398,0.0001009785,0.001378236,0.00410068,0.0002362974,0.00004900426,0.000002132417,0.00004656799,0.8681463],"genre_scores_gemma":[0.992926,0.0000374482,0.0002227808,0.00007801826,0.00002410679,0.0000043233,0.000003022188,5.440149e-7,0.006703729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8669862,"threshold_uncertainty_score":0.5457808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02310189164535432,"score_gpt":0.33551340038927,"score_spread":0.3124115087439157,"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."}}