{"id":"W4407384743","doi":"10.48550/arxiv.2502.05349","title":"Contextual Scenario Generation for Two-Stage Stochastic Programming","year":2025,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Korea Advanced Institute of Science and Technology; University of Toronto","keywords":"Stochastic programming; Computer science; Stage (stratigraphy); Mathematical optimization; Mathematics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00478646,0.001602227,0.001583656,0.0007768124,0.0005379679,0.001181672,0.001748372,0.001766179,0.004058965],"category_scores_gemma":[0.01489346,0.0009163521,0.001366329,0.00069686,0.001455603,0.001622859,0.002636105,0.003155453,0.0003753974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647339,"about_ca_system_score_gemma":0.001913673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003766809,"about_ca_topic_score_gemma":0.00435602,"domain_scores_codex":[0.9976277,0.001438491,0.00008510582,0.0004452173,0.0002440646,0.0001594557],"domain_scores_gemma":[0.9896772,0.008658805,0.0005727808,0.0003719215,0.0004047902,0.0003144428],"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":[0.00005248051,0.00003399972,0.0004794338,0.00004983148,0.00002367308,0.00003090058,0.00002706886,0.9759966,0.0001887891,0.01638964,0.0003742954,0.006353214],"study_design_scores_gemma":[0.000009046188,0.00001599665,0.00003728712,0.00000589369,0.000002529662,0.000003836989,0.000002801518,0.9891377,0.00008442116,0.0105738,0.000123634,0.000002956558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01632911,0.0002386701,0.9812797,0.0003208789,0.0000232467,0.0001024853,0.0001358039,0.000246321,0.001323828],"genre_scores_gemma":[0.6914896,0.000369853,0.3041826,0.0003346307,0.00007018633,0.0007660009,0.0007059552,0.0001661512,0.001915036],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00478646,"threshold_uncertainty_score":0.02531356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.339166986485041,"score_gpt":0.3414040096792174,"score_spread":0.002237023194176402,"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."}}