{"id":"W2981341540","doi":"10.2139/ssrn.3426207","title":"Fragmentation of Distributed Exchanges","year":2019,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; University of Toronto","funders":"","keywords":"Competitor analysis; Fragmentation (computing); De facto; Economic geography; Cluster (spacecraft); Monte Carlo method; Business; Computer science; Industrial organization; Geography; Computer network; Mathematics","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":[0.001532481,0.0002766459,0.001003679,0.002096036,0.001742536,0.003574647,0.001048741,0.001621039,0.02438403],"category_scores_gemma":[0.0163863,0.000472261,0.0006286621,0.002119759,0.002886907,0.006873553,0.002912562,0.001539753,0.001316891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590014,"about_ca_system_score_gemma":0.0007233425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00102718,"about_ca_topic_score_gemma":0.0006194642,"domain_scores_codex":[0.9990212,0.0003467695,0.00004922714,0.0002214253,0.0001559283,0.0002055943],"domain_scores_gemma":[0.9901952,0.004886081,0.001426455,0.001718753,0.0007772107,0.0009964172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002048966,0.00004508215,0.002919189,0.00006651778,0.00002645208,0.0001837042,0.0005992455,0.01308007,0.000581955,0.9660577,0.002800405,0.01343491],"study_design_scores_gemma":[0.00004292512,0.00003469237,0.002226591,0.00002606188,0.00001490867,0.0002004178,0.000420934,0.030897,0.0001873223,0.9633261,0.002612133,0.00001091643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7666807,0.001320708,0.137287,0.002954304,0.0001366245,0.00008657118,0.0005040746,0.0003075388,0.09072258],"genre_scores_gemma":[0.9875958,0.00023865,0.004247718,0.00008195846,0.00006070918,0.00003583335,0.0001469824,0.00003684144,0.007555441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02438403,"threshold_uncertainty_score":0.08157265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091173394951303,"score_gpt":0.2232427188083546,"score_spread":0.2023309848588416,"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."}}