{"id":"W1511489666","doi":"10.1287/ijoc.1080.0283","title":"Solving Lot-Sizing Problems on Parallel Identical Machines Using Symmetry-Breaking Constraints","year":2008,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Organizational Management and Leadership","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Mathematical optimization; Integer programming; Computer science; Point (geometry); Production (economics); Integer (computer science); Symmetry breaking; Algorithm; Mathematics","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009044903,0.0003570491,0.0003390296,0.0008215953,0.001496563,0.001045697,0.0004273416,0.0000991534,0.0001980353],"category_scores_gemma":[0.000474004,0.0003008374,0.0001753864,0.0007385629,0.000139382,0.001762558,0.0002192776,0.0007187788,0.0003464583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001282443,"about_ca_system_score_gemma":0.000047721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000334802,"about_ca_topic_score_gemma":0.000002562145,"domain_scores_codex":[0.9973699,0.0000177824,0.0008574339,0.000285607,0.0008095936,0.0006596115],"domain_scores_gemma":[0.9985964,0.0001756825,0.0007607606,0.0001679133,0.0002467973,0.00005248624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002344425,0.0005492798,0.3809131,0.0008743469,0.0005336164,0.0010616,0.001536647,0.262475,0.000459605,0.2596559,0.002394452,0.08931202],"study_design_scores_gemma":[0.005074431,0.0002094469,0.08239157,0.004106337,0.0002191091,0.001629759,0.002089783,0.8805884,0.00005808636,0.01039776,0.010941,0.002294352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9198515,0.00006096478,0.05136708,0.001035445,0.001561476,0.0003118315,5.787086e-7,0.0002673012,0.02554386],"genre_scores_gemma":[0.9888639,0.000006863581,0.003308509,0.00390772,0.003774239,6.404339e-7,0.000007722841,0.00005743086,0.00007300581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6181133,"threshold_uncertainty_score":0.9999913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.056480628773111,"score_gpt":0.2560955779263339,"score_spread":0.1996149491532229,"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."}}