{"id":"W785130179","doi":"10.1609/aaai.v28i1.8893","title":"Robust Winners and Winner Determination Policies under Candidate Uncertainty","year":2014,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerio de Ciencia e Innovación","keywords":"Unavailability; Voting; Computer science; Computation; Condorcet method; Majority rule; Mathematical optimization; Artificial intelligence; Algorithm; Mathematics; Statistics","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":[0.001004179,0.0001677398,0.0003012477,0.0001428102,0.0001760211,0.0001459396,0.0004117602,0.00008858108,0.00007461033],"category_scores_gemma":[0.0004486454,0.0001400728,0.00006787312,0.0002440531,0.0003063486,0.0001846225,0.00009205146,0.0001636974,0.00008183654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004123199,"about_ca_system_score_gemma":0.00001282328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000336401,"about_ca_topic_score_gemma":0.00004294339,"domain_scores_codex":[0.9987622,0.00001419021,0.0005566583,0.000342167,0.00007266124,0.0002520578],"domain_scores_gemma":[0.9990463,0.00008394186,0.0005033264,0.0001592953,0.0001455473,0.0000615896],"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":[0.00002834248,0.00002932553,0.002093707,0.00003771931,0.000009648481,2.901195e-8,0.0009568996,0.0003749171,0.001543234,0.9907346,0.00003779145,0.004153794],"study_design_scores_gemma":[0.00006837684,0.0001950484,0.00283322,0.0002114193,0.00001292614,0.000004916955,0.001639341,0.07823429,0.03104829,0.884701,0.0006867031,0.0003645261],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599462,0.00003460053,0.004131026,0.002612136,0.0003835343,0.000245666,0.00001814128,0.00004073221,0.032588],"genre_scores_gemma":[0.9987698,0.00002236403,0.0001429014,0.00023748,0.00009098307,0.0000118447,8.206086e-7,0.00001411428,0.00070967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1060336,"threshold_uncertainty_score":0.5712004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0977726672521633,"score_gpt":0.2617441265676452,"score_spread":0.1639714593154819,"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."}}