{"id":"W27038116","doi":"10.1093/jnci/djw115","title":"Polyhedral Approaches to Machine Scheduling","year":2008,"lang":"en","type":"article","venue":"","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Polyhedron; Scheduling (production processes); Mathematical optimization; Polyhedral combinatorics; Mathematical proof; Travelling salesman problem; Computer science; Cutting-plane method; Mathematics; Algorithm; Combinatorics; Integer programming; Regular polygon; Convex optimization","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":[],"consensus_categories":[],"category_scores_codex":[0.00004622385,0.00009807781,0.0000930612,0.00008202044,0.00006726612,0.00001510756,0.00008892483,0.00004170365,0.000157685],"category_scores_gemma":[0.00001489564,0.00009154917,0.00003119847,0.0002114332,0.00001183008,0.00006242812,0.00001672493,0.0000854067,0.0002651241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001839539,"about_ca_system_score_gemma":0.000007340499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009246759,"about_ca_topic_score_gemma":0.000002552753,"domain_scores_codex":[0.9994969,0.00000514154,0.0001161024,0.0001119501,0.000096051,0.0001738952],"domain_scores_gemma":[0.9997231,0.00001217142,0.000005338976,0.0001323268,0.00001008651,0.0001169355],"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":[0.000002016622,0.00001029433,0.0006667683,0.00000520747,0.00001229059,0.000004129716,0.000288132,0.9957371,0.00009007174,0.0006377365,0.0001853658,0.002360829],"study_design_scores_gemma":[0.000146885,0.000009977575,0.0004545612,0.000003620226,0.000002517413,0.00002490208,0.00005059586,0.9958233,0.002941719,0.00001608068,0.0003718254,0.0001540159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1551551,0.0002853062,0.8173701,0.0003534493,0.0003216325,0.00009948913,0.000002565953,0.001161856,0.02525051],"genre_scores_gemma":[0.5720232,0.00001080573,0.4270944,0.0001168601,0.00008042951,0.000006139547,0.000005356456,0.00001960672,0.0006431268],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4168681,"threshold_uncertainty_score":0.3733267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07337646448938698,"score_gpt":0.2119761857776887,"score_spread":0.1385997212883018,"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."}}