{"id":"W3124756266","doi":"","title":"The market microstructure approach to foreign exchange - Looking back and looking forward","year":2012,"lang":"en","type":"preprint","venue":"BIBSYS Brage (BIBSYS (Norway))","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Market microstructure; Market liquidity; Electronic trading; Exchange rate; Foreign exchange market; Currency; Price discovery; Order (exchange); Transaction cost; Business; Transparency (behavior); Monetary economics; Economics; Private information retrieval; Financial economics; Microeconomics; Finance; Computer science; Futures contract","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002282901,0.001096488,0.001961109,0.001012458,0.0009675871,0.001562528,0.001482376,0.0008070019,0.002979037],"category_scores_gemma":[0.0001765651,0.001001676,0.0007189589,0.001144252,0.0002010426,0.0003547963,0.002830041,0.001080416,0.0009589518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003398727,"about_ca_system_score_gemma":0.00005437395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001742295,"about_ca_topic_score_gemma":0.0003771869,"domain_scores_codex":[0.9942613,0.0001471064,0.001909074,0.001917234,0.000239141,0.001526113],"domain_scores_gemma":[0.9953216,0.0002323946,0.001495716,0.002225503,0.0001727929,0.0005519685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000835975,0.0008673426,0.08876523,0.01497871,0.00910185,0.00008352082,0.02067701,0.002414695,0.0004089386,0.3828343,0.4073662,0.07166632],"study_design_scores_gemma":[0.001294443,0.0001049632,0.03667481,0.0004499264,0.0002907135,0.0001300295,0.001437499,0.00824314,0.00003756098,0.02731965,0.9209579,0.003059426],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05010544,0.09619122,0.05639744,0.001146639,0.00470718,0.005954643,0.0051228,0.0002616664,0.780113],"genre_scores_gemma":[0.9485628,0.002292475,0.00516131,0.0005828387,0.002499212,0.0004831843,0.0003271324,0.0003388666,0.03975216],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8984573,"threshold_uncertainty_score":0.9998189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587707293313366,"score_gpt":0.2106015636011428,"score_spread":0.1847244906680091,"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."}}