{"id":"W3085334717","doi":"10.1080/10556788.2020.1817447","title":"Improving dynamic programming for travelling salesman with precedence constraints: parallel Morin–Marsten bounding","year":2020,"lang":"en","type":"article","venue":"Optimization methods & software","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bounding overwatch; Travelling salesman problem; Morin; Computer science; Mathematical optimization; Mathematics; Algorithm; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.001215709,0.0004667733,0.0005298492,0.0001487771,0.0003665403,0.0003017331,0.0003655123,0.0002256769,0.00006535485],"category_scores_gemma":[0.001505348,0.000488814,0.000129232,0.0008074144,0.0001499834,0.0005140295,0.00005690551,0.0003729117,0.000003107051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001748725,"about_ca_system_score_gemma":0.0001048576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002760497,"about_ca_topic_score_gemma":0.000002103689,"domain_scores_codex":[0.9973738,0.0003096477,0.000681359,0.0006810733,0.0002843524,0.0006697482],"domain_scores_gemma":[0.997986,0.0008214994,0.0002546147,0.0003351253,0.0002941051,0.0003087053],"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":[0.00003732831,0.00001184586,0.0003075939,0.0003833586,0.00006461933,0.000002622287,0.0008769117,0.8145658,0.0005142229,0.00006773654,0.000007505503,0.1831605],"study_design_scores_gemma":[0.0009590742,0.0001268706,0.00002870076,0.0001415727,0.0001213104,0.00001929875,0.000411862,0.9963295,0.0008795582,0.0000445353,0.0003346601,0.0006030009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002943512,0.0002121103,0.9956567,0.0001363113,0.0002542092,0.00129486,0.0000299675,0.002005277,0.0001161895],"genre_scores_gemma":[0.005610716,0.00006187521,0.9934047,0.0001242073,0.0001167353,0.0002664947,0.0001319662,0.0002398658,0.0000434774],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1825575,"threshold_uncertainty_score":0.9997563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520931664539284,"score_gpt":0.301731733635452,"score_spread":0.2765224169900592,"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."}}