{"id":"W2463032555","doi":"","title":"A characterization of voting power for discrete weight distributions","year":2016,"lang":"en","type":"article","venue":"International Joint Conference on Artificial Intelligence","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Voting; Shapley value; Power index; Mathematical economics; Power (physics); Value (mathematics); Weighted voting; Mathematical optimization; Game theory; Mathematics; Computer science; Statistics","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":[0.006409725,0.0008495362,0.001286414,0.002037418,0.0009240514,0.003305338,0.002942698,0.001601734,0.007931812],"category_scores_gemma":[0.04953845,0.000640436,0.001085949,0.002367055,0.0044398,0.00729306,0.001863232,0.002358904,0.0006850978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002239028,"about_ca_system_score_gemma":0.0008513486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001252763,"about_ca_topic_score_gemma":0.0005890993,"domain_scores_codex":[0.9951721,0.001919513,0.0002547783,0.000928993,0.000981253,0.000743394],"domain_scores_gemma":[0.9697317,0.02229788,0.003391806,0.002230676,0.001383247,0.0009646432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009598403,0.00006613037,0.002258355,0.0000817402,0.00004666357,0.0001204078,0.0004169112,0.08997986,0.0021824,0.8898451,0.0006690859,0.0142374],"study_design_scores_gemma":[0.00003165716,0.00007079574,0.001049542,0.0000317196,0.00001364995,0.0001457109,0.0001115549,0.4367729,0.0007065535,0.5596999,0.001334768,0.00003120729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1890464,0.0002896229,0.7907701,0.0006383977,0.00004396167,0.0001659322,0.0003157526,0.0001216348,0.0186082],"genre_scores_gemma":[0.9620994,0.0002706067,0.03285526,0.0001159635,0.00008700956,0.0001981421,0.0002171377,0.00007837461,0.004078095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007931812,"threshold_uncertainty_score":0.03389823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029634677157848,"score_gpt":0.2876688554881278,"score_spread":0.184705387772343,"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."}}