{"id":"W2015373604","doi":"10.1017/s1049096512001497","title":"CLOSENESS COUNTS IN HORSE SHOES, DANCING, AND FORECASTING","year":2013,"lang":"en","type":"article","venue":"PS Political Science & Politics","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convention; Quarter (Canadian coin); Closeness; Democracy; Economics; Political science; Law; History; Politics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001984265,0.0004129888,0.0004672962,0.002647027,0.0008556675,0.002231102,0.0006469816,0.000778465,0.01353976],"category_scores_gemma":[0.01821782,0.0002968396,0.0003511578,0.003157418,0.0005232118,0.00209671,0.001323086,0.001402981,0.002908774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001029189,"about_ca_system_score_gemma":0.0003976515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02235192,"about_ca_topic_score_gemma":0.03532758,"domain_scores_codex":[0.9985329,0.0007002674,0.00008243872,0.0002610833,0.0003061215,0.0001171159],"domain_scores_gemma":[0.9950784,0.002950439,0.0005017595,0.0003308514,0.0006203604,0.0005180999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007582413,0.0003009276,0.6927214,0.0001289749,0.0001693338,0.0002556167,0.001659605,0.07030945,0.0003494449,0.03936787,0.04487893,0.1491002],"study_design_scores_gemma":[0.00006380085,0.0003731691,0.3223577,0.0001901906,0.00008098417,0.0001526894,0.005591386,0.5699568,0.0008948001,0.0475311,0.05267216,0.0001350417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.873016,0.001410638,0.02478198,0.005396688,0.0006295475,0.0001327482,0.006338525,0.0005195275,0.08777431],"genre_scores_gemma":[0.9867291,0.0001978686,0.003671398,0.00009693405,0.00009183985,0.0000306642,0.00246341,0.0000415957,0.006677045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02235192,"threshold_uncertainty_score":0.045295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06573288199459737,"score_gpt":0.3672505542417221,"score_spread":0.3015176722471247,"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."}}