{"id":"W2949433202","doi":"10.48550/arxiv.1404.7325","title":"Tight Bounds for Restricted Grid Scheduling","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Syddansk Universitet; University of Waterloo; University of Toronto; Danmarks Frie Forskningsfond; Villum Fonden","keywords":"Bin; Bin packing problem; Grid; Upper and lower bounds; Competitive analysis; Matching (statistics); Online algorithm; Scheduling (production processes); Integer (computer science); Computer science; Mathematics; Mathematical optimization; Combinatorics; Algorithm; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0002917019,0.0002425234,0.0002749412,0.0003270538,0.0002654183,0.0002972797,0.001823755,0.0002836646,0.00002358227],"category_scores_gemma":[0.0001004223,0.0002770717,0.0001928698,0.0005729073,0.00007536719,0.0003181561,0.001298549,0.0004444804,0.00006245641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000141229,"about_ca_system_score_gemma":0.000303358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003432565,"about_ca_topic_score_gemma":0.000009949926,"domain_scores_codex":[0.9981951,0.0001277962,0.0002023675,0.0009691215,0.000102255,0.0004033905],"domain_scores_gemma":[0.9980274,0.0001604458,0.0002071305,0.001048076,0.0003459278,0.0002110568],"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":[0.00001644323,0.00004792872,0.0002412441,0.00008621058,0.00004559767,0.00002027803,0.00008420823,0.7162318,0.00001908191,0.281415,0.001439067,0.0003530936],"study_design_scores_gemma":[0.0005487581,0.0000579374,0.0001318819,0.00005804066,0.00002068771,0.000001188521,0.000008263984,0.9593199,0.00005094048,0.03044603,0.009033709,0.0003226747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01074122,0.00002779491,0.9843071,0.000317703,0.0009277879,0.0004732192,0.00001427729,0.000361384,0.002829494],"genre_scores_gemma":[0.9280289,0.000160468,0.06714877,0.000239634,0.0002382621,0.000004339496,0.00007916798,0.00002629688,0.0040742],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9172876,"threshold_uncertainty_score":0.9999682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08947936903725882,"score_gpt":0.2088021905716253,"score_spread":0.1193228215343665,"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."}}