{"id":"W1504426303","doi":"10.5750/jpm.v6i3.592","title":"LONG-TERM PREDICTION MARKETS","year":2013,"lang":"en","type":"article","venue":"The Journal of Prediction Markets","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Portfolio; Economics; Financial market; Outcome (game theory); Term (time); Prediction market; Time horizon; Market liquidity; Horizon; Financial economics; Constraint (computer-aided design); Market impact; Cash; Econometrics; Microeconomics; Monetary economics; Market microstructure; Finance","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":[0.002910176,0.0006949579,0.0008540538,0.0004088634,0.00096657,0.003480774,0.002612743,0.002619896,0.02019942],"category_scores_gemma":[0.01579224,0.0003152015,0.0007230579,0.0004683908,0.001860228,0.00846775,0.002132453,0.002084219,0.00118287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001280518,"about_ca_system_score_gemma":0.0008908046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001775835,"about_ca_topic_score_gemma":0.0009753825,"domain_scores_codex":[0.9989092,0.0002078053,0.00005563633,0.0003173297,0.0003185396,0.0001914389],"domain_scores_gemma":[0.9948604,0.002476655,0.001214294,0.0004631666,0.0005993238,0.0003861978],"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":[0.00009124752,0.00008332303,0.002970127,0.00009515326,0.00003956279,0.0002472147,0.0001744928,0.03047169,0.00104208,0.9412788,0.002771345,0.02073491],"study_design_scores_gemma":[0.00004487878,0.00009313316,0.00184554,0.00004148178,0.00001992108,0.0001257416,0.0001214603,0.2117641,0.0005928585,0.7794945,0.005814312,0.00004205642],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2431018,0.002928794,0.6556889,0.007306371,0.0004942731,0.0002632262,0.001218405,0.0007247662,0.08827353],"genre_scores_gemma":[0.9717019,0.000684652,0.01512635,0.0002655875,0.0002330469,0.0001224532,0.0002396148,0.00005168524,0.01157462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02019942,"threshold_uncertainty_score":0.06757379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650538138600701,"score_gpt":0.2030008885685492,"score_spread":0.1864955071825422,"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."}}