{"id":"W4395096251","doi":"10.2139/ssrn.4806224","title":"A Bi-Objective Model and a Branch-and-Price-and-Cut Solution Method for the Railroad Blocking Problem in Hazardous Material Transportation","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Hazardous waste; Blocking (statistics); Branch and cut; Computer science; Mathematical optimization; Engineering; Mathematics; Integer programming; Waste management; Computer network","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":[0.002250835,0.001401687,0.002262481,0.001144225,0.000757293,0.001912869,0.002292193,0.002834468,0.008470276],"category_scores_gemma":[0.003237688,0.001245701,0.001659632,0.002028513,0.0008947384,0.001672714,0.001267866,0.003257013,0.0006923249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167683,"about_ca_system_score_gemma":0.003030941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02367575,"about_ca_topic_score_gemma":0.01733204,"domain_scores_codex":[0.9991828,0.0003837988,0.00003103961,0.0001010614,0.0001947167,0.0001065283],"domain_scores_gemma":[0.9984978,0.001084237,0.00009267846,0.00003936446,0.0002034291,0.00008240108],"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":[0.00002271452,0.00004064608,0.00008476607,0.0000469997,0.00001678726,0.00002245088,0.00001391811,0.9868643,0.0001889203,0.006578115,0.0004217679,0.005698569],"study_design_scores_gemma":[0.000005829061,0.00001009583,0.00002429755,0.000003399814,0.000005932504,0.000002869814,0.000003289078,0.9980351,0.00002565914,0.001758388,0.0001224941,0.000002724782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01187444,0.0003294478,0.9822837,0.000292036,0.00006001573,0.0001129628,0.0001891131,0.0001127293,0.00474558],"genre_scores_gemma":[0.4635841,0.001226359,0.5198034,0.0001883762,0.0001420728,0.0009292784,0.0006031302,0.0002227965,0.01330042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02367575,"threshold_uncertainty_score":0.04707587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03270231503789257,"score_gpt":0.3493294684504715,"score_spread":0.316627153412579,"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."}}