{"id":"W2027580141","doi":"10.1016/j.tre.2011.06.001","title":"A bi-objective model for planning and managing rail-truck intermodal transportation of hazardous materials","year":2011,"lang":"en","type":"article","venue":"Transportation Research Part E Logistics and Transportation Review","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":136,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Memorial University of Newfoundland","funders":"U.S. Department of Transportation; U.S. Department of Energy","keywords":"Train; Hazardous waste; Tabu search; Truck; Transport engineering; Scheduling (production processes); Routing (electronic design automation); Computer science; Operations research; Route planning; Transportation planning; Engineering; Automotive engineering; Computer network; Operations management; Waste management","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":[0.004162688,0.0002808036,0.0009097388,0.0004918579,0.0003004335,0.00006942658,0.0003119718,0.0001374545,0.0001904877],"category_scores_gemma":[0.0002777635,0.0002345667,0.0002085054,0.0008176973,0.0004493681,0.0003853003,0.000002664425,0.0002195089,0.000004255401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001581813,"about_ca_system_score_gemma":0.0001138312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003167345,"about_ca_topic_score_gemma":0.001297074,"domain_scores_codex":[0.9954749,0.0002359404,0.001933761,0.0007665936,0.001172126,0.000416647],"domain_scores_gemma":[0.9968705,0.0006888325,0.0005811908,0.0003617172,0.001284824,0.0002130039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.006162427,0.001120006,0.1794262,0.02586454,0.001626269,0.0003176314,0.1156321,0.02461392,0.002866598,0.4378101,0.003694824,0.2008654],"study_design_scores_gemma":[0.003192736,0.0008706834,0.6998215,0.00414893,0.001598846,0.000003165432,0.004889193,0.02664425,0.002057771,0.252581,0.00304855,0.001143356],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2551516,0.01308641,0.7236768,0.001014809,0.0001805123,0.002853899,0.003581121,0.00007260626,0.0003822684],"genre_scores_gemma":[0.9663561,0.02647366,0.00599266,0.0001086544,0.00002466826,0.0002229003,0.0006393287,0.00002855379,0.0001534679],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7176841,"threshold_uncertainty_score":0.956535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3712277821255654,"score_gpt":0.4621481738678355,"score_spread":0.09092039174227012,"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."}}