{"id":"W2473424882","doi":"10.3329/ganit.v34i0.28549","title":"A New Decomposition-Based Pricing Technique For Solving Large-Scale Mixed IP with a Computer Technique","year":2016,"lang":"en","type":"article","venue":"GANIT Journal of Bangladesh Mathematical Society","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Decomposition; Integer programming; Computer science; Scale (ratio); Benders' decomposition; Mathematical optimization; Decomposition method (queueing theory); Filter (signal processing); Algorithm; Mathematics; Statistics","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":[0.0007436483,0.0006985802,0.0006888099,0.0008210595,0.000616052,0.0008210764,0.001078996,0.0006912272,0.005493884],"category_scores_gemma":[0.001893293,0.0004239803,0.001128874,0.0009366233,0.0008355878,0.00166328,0.001519572,0.002828263,0.001108531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000442686,"about_ca_system_score_gemma":0.001081101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001162372,"about_ca_topic_score_gemma":0.001210633,"domain_scores_codex":[0.9994029,0.0001729447,0.00002810261,0.00008979612,0.0002447095,0.00006155526],"domain_scores_gemma":[0.9994367,0.0002508111,0.00004149047,0.0001222737,0.000110509,0.00003815579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000117352,0.000246672,0.000530662,0.0002871557,0.00009495654,0.0002117756,0.0001920036,0.205851,0.02496537,0.5502387,0.01079605,0.2064682],"study_design_scores_gemma":[0.00002999349,0.00005585978,0.0001141443,0.0000160384,0.00001815261,0.0001395181,0.00001997703,0.9009266,0.003016079,0.08515248,0.01049489,0.00001614561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001219602,0.00003530776,0.9968922,0.00006655029,0.0000242748,0.00001887727,0.000009889601,0.0001044602,0.001628964],"genre_scores_gemma":[0.06218228,0.0001541457,0.9337491,0.0001848384,0.00007594345,0.0001805856,0.00007357723,0.000160411,0.003239095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005493884,"threshold_uncertainty_score":0.01837885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008430422427400646,"score_gpt":0.2284485718426546,"score_spread":0.220018149415254,"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."}}