{"id":"W4404351471","doi":"10.1145/3677052.3698665","title":"Optimizing Sequential Predictions for Order Execution: a Decision Focused Learning Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Universitas Brawijaya","keywords":"Computer science; Order (exchange); Machine learning; Artificial intelligence","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":[0.002253742,0.001123702,0.001545739,0.0007007682,0.0003648339,0.001022725,0.001627023,0.001340877,0.002290218],"category_scores_gemma":[0.006272354,0.0006933823,0.0005631577,0.0007076423,0.0009179788,0.001493858,0.0008760627,0.001605544,0.0003222456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001253621,"about_ca_system_score_gemma":0.00176557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006158704,"about_ca_topic_score_gemma":0.005351171,"domain_scores_codex":[0.9992701,0.0002724061,0.00003805336,0.0001775689,0.0001290915,0.0001127101],"domain_scores_gemma":[0.9965227,0.002465223,0.0003349421,0.0001760082,0.000350933,0.0001501672],"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":[0.00006443271,0.00008804824,0.001210994,0.00003941669,0.00003726711,0.00003920128,0.00004489436,0.961696,0.0005318865,0.005331395,0.0004979218,0.03041853],"study_design_scores_gemma":[0.000004220973,0.00001615343,0.00005100595,0.000002243981,0.000002808034,0.000002562033,0.000002349834,0.9978915,0.0001028714,0.001868503,0.00005346148,0.000002321966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05317082,0.0004510832,0.9428341,0.0008879192,0.00003925237,0.00007027539,0.00009873655,0.0004196842,0.002028211],"genre_scores_gemma":[0.8917336,0.0002612037,0.1052736,0.0003167737,0.0001070707,0.0001299322,0.0001837489,0.00006371777,0.001930329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006158704,"threshold_uncertainty_score":0.01224571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1331572047805162,"score_gpt":0.427203518293121,"score_spread":0.2940463135126047,"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."}}