{"id":"W4321123803","doi":"10.3934/mbe.2023323","title":"A method for demand-accurate one-dimensional cutting problems with pattern reduction","year":2023,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Optimization and Packing Problems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Benchmark (surveying); Reduction (mathematics); Computer science; Mathematical optimization; Focus (optics); Variable (mathematics); Software; Integer (computer science); Constant (computer programming); 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":[0.0005285098,0.001056443,0.0009736277,0.001254,0.0004614741,0.000772702,0.00161066,0.0008293857,0.004970016],"category_scores_gemma":[0.001680749,0.0006115481,0.001604696,0.001610134,0.0004525448,0.0009989419,0.001230978,0.001909022,0.001320781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004738159,"about_ca_system_score_gemma":0.001142474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001993084,"about_ca_topic_score_gemma":0.002228662,"domain_scores_codex":[0.9994537,0.00009629982,0.00003140886,0.00008457688,0.0002909664,0.000042954],"domain_scores_gemma":[0.9994929,0.0002312976,0.00004435403,0.00008783548,0.0001193257,0.00002439408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008530689,0.0001971972,0.0004920904,0.0005081653,0.00008622558,0.0001828997,0.000116547,0.4437187,0.01411346,0.04026021,0.01013045,0.4901086],"study_design_scores_gemma":[0.00003001557,0.00005616718,0.0001266526,0.00002390636,0.00001932526,0.0001260157,0.00001793086,0.9752807,0.002436308,0.013265,0.008604613,0.00001345657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001643936,0.0001464264,0.9957421,0.00006434851,0.00005108677,0.00006085856,0.00004090525,0.0003272275,0.001923025],"genre_scores_gemma":[0.04102065,0.0003012388,0.9544786,0.00008546413,0.00005744525,0.000339017,0.0002689834,0.0002507311,0.003197827],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004970016,"threshold_uncertainty_score":0.01662636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02667845461683185,"score_gpt":0.2563763116623132,"score_spread":0.2296978570454814,"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."}}