{"id":"W4417517894","doi":"10.33545/27075923.2020.v1.i2a.110","title":"Integrating AI-powered market microstructure analytics into cloud-based high-frequency trading platforms","year":2020,"lang":"","type":"article","venue":"International Journal of Circuit Computing and Networking","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Algorithmic trading; Analytics; Market microstructure; High-frequency trading; Trading strategy; Cloud computing; Predictive analytics; Volatility (finance); Market liquidity","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.009645005,0.0007501145,0.001457667,0.0009274352,0.0006803017,0.00221814,0.002957525,0.0004078815,0.0003502755],"category_scores_gemma":[0.006897771,0.0006492959,0.0007071335,0.001548465,0.0003903187,0.0006929549,0.0005075103,0.002454303,0.000003890287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004476037,"about_ca_system_score_gemma":0.0007511984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004197605,"about_ca_topic_score_gemma":0.00001139236,"domain_scores_codex":[0.9902045,0.0007397601,0.004069755,0.0009910929,0.003159553,0.000835372],"domain_scores_gemma":[0.9853634,0.006346709,0.004747172,0.0003635245,0.002436391,0.0007428034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007690392,0.00007539064,0.06549121,0.00008210634,0.0009468755,0.0006454783,0.007512342,0.00885431,0.002218586,0.001806666,0.002882171,0.9087158],"study_design_scores_gemma":[0.003367482,0.0006445735,0.006119126,0.003791927,0.0002908912,0.001216118,0.001503759,0.8925681,0.0003724956,0.08563046,0.003511378,0.0009837528],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2753558,0.00367435,0.6968114,0.003358977,0.01900263,0.0002203308,0.00001836563,0.00005328938,0.001504885],"genre_scores_gemma":[0.9506515,0.0001063094,0.03530151,0.002858368,0.01098392,5.125278e-7,0.000005814953,0.00007444858,0.00001767849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9077321,"threshold_uncertainty_score":0.9998471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0619161943371091,"score_gpt":0.347964715946259,"score_spread":0.2860485216091499,"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."}}