{"id":"W2098362771","doi":"10.1007/s00191-011-0230-8","title":"Efficiency of continuous double auctions under individual evolutionary learning with full or limited information","year":2011,"lang":"en","type":"article","venue":"Journal of Evolutionary Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; Concordia University; Universiteit van Amsterdam; University of Technology Sydney","keywords":"Allocative efficiency; Common value auction; Microeconomics; Outcome (game theory); Economics; Transparency (behavior); Counterfactual thinking; Double auction; Perfect information; Order (exchange); Computer science; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006696044,0.0005258146,0.001363242,0.0006186418,0.0003710614,0.001851492,0.001301963,0.001045304,0.001721245],"category_scores_gemma":[0.02873632,0.0004129093,0.0006243748,0.0004257967,0.001980614,0.003019056,0.001330119,0.0008490611,0.0002337517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093225,"about_ca_system_score_gemma":0.001045692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009802412,"about_ca_topic_score_gemma":0.0004808338,"domain_scores_codex":[0.9978099,0.001104359,0.0001371804,0.0003090863,0.0003465774,0.0002928858],"domain_scores_gemma":[0.9758658,0.0168804,0.003599639,0.002112088,0.000877462,0.0006645281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005251745,0.0003199567,0.005823709,0.0001206925,0.0001540921,0.0001456896,0.0001504788,0.8884197,0.002636745,0.08196444,0.0003142147,0.01942517],"study_design_scores_gemma":[0.00006897815,0.0001043252,0.001271631,0.000007853432,0.00001366955,0.00003381831,0.00002636031,0.9379045,0.0006340174,0.0598531,0.00006916714,0.00001256561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7949801,0.0001743393,0.1993746,0.0004260998,0.00001227815,0.0000739825,0.00008718033,0.0001117455,0.004759445],"genre_scores_gemma":[0.9888335,0.00006090788,0.00991658,0.0000382879,0.00001039122,0.00005826349,0.00004080105,0.0000157826,0.001025381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006696044,"threshold_uncertainty_score":0.03541249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04293938033080552,"score_gpt":0.1979035056966514,"score_spread":0.1549641253658458,"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."}}