{"id":"W2611924894","doi":"","title":"Branch-and-cut-and-price for the traveling salesman problem with time windows","year":2009,"lang":"en","type":"article","venue":"","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Transport Canada","funders":"","keywords":"Travelling salesman problem; Computer science; Mathematics; Algorithm","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":[0.002216842,0.0001231859,0.0001979572,0.00007974826,0.0005305971,0.0003226349,0.0002994419,0.00005097886,0.00008077698],"category_scores_gemma":[0.0005638228,0.00005896836,0.00005614875,0.0004305586,0.00010779,0.0001698073,0.00002604863,0.0001120906,0.00008786026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006977489,"about_ca_system_score_gemma":0.00005391125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001801056,"about_ca_topic_score_gemma":0.00002604281,"domain_scores_codex":[0.9985791,0.00004407216,0.0002911087,0.0003737092,0.0004281065,0.0002838411],"domain_scores_gemma":[0.9973233,0.001977497,0.00009022045,0.0003294061,0.0001769366,0.0001026288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007281134,0.0004326376,0.008821463,0.0000247174,0.0003790204,0.00000695964,0.007062953,0.01339351,0.007643567,0.1898057,0.0235109,0.7481904],"study_design_scores_gemma":[0.006574472,0.001730074,0.1199174,0.0001633491,0.0005156281,0.0003495608,0.00200837,0.3640473,0.003245877,0.3905055,0.1093998,0.001542606],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3204595,0.001784599,0.5920852,0.04577873,0.0001808121,0.001683701,0.00002015074,0.0003441445,0.0376632],"genre_scores_gemma":[0.9605695,0.00001872271,0.02823659,0.0008824303,0.00009523863,0.00001663914,0.000001229364,0.00000836091,0.01017126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7466478,"threshold_uncertainty_score":0.4080977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06432540089113045,"score_gpt":0.33557207073282,"score_spread":0.2712466698416895,"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."}}