{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009077874,0.0002391353,0.0003423766,0.0004181692,0.0003580756,0.0002933188,0.001007152,0.0002399054,0.0001144698],"category_scores_gemma":[0.0005474118,0.0002458684,0.0002916732,0.0006959281,0.000110131,0.0001679798,0.0005767829,0.0002875531,0.00004361456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175343,"about_ca_system_score_gemma":0.0002886819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001328912,"about_ca_topic_score_gemma":0.0002139872,"domain_scores_codex":[0.9978524,0.00009991869,0.0004459472,0.001151679,0.0001958751,0.0002541141],"domain_scores_gemma":[0.9969324,0.000728309,0.0004100758,0.001054598,0.0007634223,0.000111208],"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":[0.00003703891,0.00007361585,0.0002679422,0.00001469869,0.0000325486,0.000003094061,0.0001188743,0.7024311,0.00007784105,0.2830316,0.001906259,0.0120054],"study_design_scores_gemma":[0.0005445913,0.00003447214,0.00004491862,0.00003301445,0.00006712823,3.139612e-7,0.0002358581,0.9352481,0.0001582021,0.04606342,0.01729207,0.0002779412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05998381,0.00002363519,0.936442,0.0001427639,0.0002905405,0.001525172,0.0002045584,0.0002013548,0.001186212],"genre_scores_gemma":[0.9678676,0.000003973751,0.003991806,0.0001106168,0.0001537605,0.0000276254,0.0001227332,0.00001193267,0.02771002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9324502,"threshold_uncertainty_score":0.9999993,"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."}}