{"id":"W1832659264","doi":"10.5555/2034396.2034526","title":"Social distance games","year":2011,"lang":"en","type":"article","venue":"","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Closeness; Transferable utility; Mathematical economics; Computer science; Context (archaeology); Stability (learning theory); Perspective (graphical); Social Welfare; Measure (data warehouse); Microeconomics; Game theory; Economics; Mathematics; Artificial intelligence; Machine learning; Data mining; Political science","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":[0.002458283,0.001212419,0.001307278,0.001118734,0.001806486,0.003733552,0.00218944,0.002322412,0.008210889],"category_scores_gemma":[0.009334326,0.0003921347,0.0009186193,0.001327288,0.003903866,0.005849279,0.003417684,0.002480933,0.001195343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002468885,"about_ca_system_score_gemma":0.001195256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001784031,"about_ca_topic_score_gemma":0.001287596,"domain_scores_codex":[0.9951484,0.00231293,0.0002773466,0.0008139156,0.001074064,0.0003733612],"domain_scores_gemma":[0.995286,0.002923809,0.000377309,0.0004513391,0.0005208113,0.0004406228],"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":[0.000009771515,0.0000170812,0.0001033964,0.0000317605,0.00001184541,0.00003704294,0.0001241515,0.005198732,0.0001550226,0.9887083,0.0008207696,0.004782268],"study_design_scores_gemma":[0.0000188636,0.00002260547,0.0000653313,0.00001737077,0.000008577271,0.0000665745,0.0001071232,0.02642087,0.0001307414,0.9604721,0.01266054,0.000009349619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04325078,0.001262519,0.8453456,0.004038993,0.0002954155,0.0004999096,0.0005171429,0.0001331877,0.1046564],"genre_scores_gemma":[0.800513,0.001619113,0.1581245,0.001202211,0.0003064018,0.0008838281,0.0005921965,0.0000994465,0.03665928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008210889,"threshold_uncertainty_score":0.0274682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08985606472725295,"score_gpt":0.2241985203543408,"score_spread":0.1343424556270879,"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."}}