{"id":"W2971843904","doi":"10.48550/arxiv.1909.00510","title":"A Geometrical Branch-and-Price (GEOM-BP) Algorithm for Big Bin Packing Problems","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Bin; Bin packing problem; Algorithm; Computer science; Combinatorics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007390847,0.0008959967,0.001181759,0.001002831,0.0005946205,0.001079799,0.001600239,0.001415903,0.004071087],"category_scores_gemma":[0.00216877,0.0005443451,0.0005991337,0.002303902,0.0006670246,0.001428775,0.001650448,0.001777583,0.001052591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006606476,"about_ca_system_score_gemma":0.001207753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001432043,"about_ca_topic_score_gemma":0.001514657,"domain_scores_codex":[0.9994661,0.0001689406,0.00002491438,0.00008963444,0.0001845959,0.00006580243],"domain_scores_gemma":[0.9994368,0.0003078202,0.0000592312,0.00007906752,0.00007339967,0.00004372474],"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":[0.0002025068,0.0001825464,0.0005968555,0.0002399085,0.00004565807,0.0001314307,0.00008950147,0.5289247,0.004268698,0.04072495,0.008153929,0.4164393],"study_design_scores_gemma":[0.00003335294,0.00005126684,0.00012837,0.00001335901,0.000008352537,0.00006499124,0.0000120172,0.9783663,0.001005584,0.01810754,0.002200491,0.000008420633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01196789,0.0004462512,0.9828395,0.0002283096,0.0000674891,0.00008354002,0.00008252896,0.0008655006,0.003418961],"genre_scores_gemma":[0.1220416,0.0003156731,0.87464,0.0001357268,0.00007157642,0.0001881392,0.0004060389,0.0002178539,0.001983484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004071087,"threshold_uncertainty_score":0.01361912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06316971932415162,"score_gpt":0.1780288936672934,"score_spread":0.1148591743431418,"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."}}