{"id":"W2741216165","doi":"10.24963/ijcai.2017/39","title":"Convergence and Quality of Iterative Voting Under Non-Scoring Rules","year":2017,"lang":"en","type":"article","venue":"","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Hebrew University of Jerusalem","keywords":"Voting; Computer science; Convergence (economics); Anti-plurality voting; Veto; Heuristic; Quality (philosophy); Scoring rule; Social choice theory; Iterative and incremental development; Process (computing); Approval voting; Cardinal voting systems; Mathematical optimization; Artificial intelligence; Mathematical economics; Machine learning; Mathematics; Economics; Political science; 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":[0.00107527,0.000073685,0.0002816559,0.00003989564,0.000196278,0.0000818699,0.0001597726,0.0000399641,0.0001038617],"category_scores_gemma":[0.0001774007,0.00007596901,0.00003977798,0.00001632399,0.0001013132,0.000232257,0.00007582235,0.00005473072,0.00007071946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001038142,"about_ca_system_score_gemma":0.000003811615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008800575,"about_ca_topic_score_gemma":0.00003879158,"domain_scores_codex":[0.9992349,0.00001605562,0.0004156046,0.0001987145,0.00001621844,0.0001185114],"domain_scores_gemma":[0.9990551,0.00008325746,0.0005456132,0.0002608034,0.00002180543,0.00003343636],"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":[0.000003792715,0.000007074602,0.3230628,0.00004045583,0.00001362058,1.17556e-7,0.0003693636,0.000006247677,0.0002245499,0.6761916,0.000004012546,0.00007630706],"study_design_scores_gemma":[0.0004671806,0.00003487692,0.9493394,0.00007676803,0.000002440876,0.000001175604,0.0004781515,0.002242176,0.00283018,0.04408112,0.0002173868,0.0002291524],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9369423,0.0001415212,0.009787831,0.00005927276,0.0002542559,0.00006417739,0.00002021391,0.00001027086,0.0527202],"genre_scores_gemma":[0.9975528,0.00001273477,0.0004651177,0.00002577564,0.00004445306,0.000002476727,7.614022e-7,0.000006012068,0.001889893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6321105,"threshold_uncertainty_score":0.3097926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1200660449642099,"score_gpt":0.3026411117150827,"score_spread":0.1825750667508728,"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."}}