{"id":"W4403133180","doi":"10.1155/2024/1850690","title":"Optimal Design of a Hazardous Materials Transportation Network considering Uncertainty in Accident Consequences","year":2024,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Hazardous waste; Accident (philosophy); Forensic engineering; Transport engineering; Environmental science; Engineering; Computer science; Risk analysis (engineering); Waste management; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002972301,0.0001564515,0.000626348,0.0004882682,0.00005091619,0.00009528445,0.0002595519,0.00008300145,0.00017939],"category_scores_gemma":[0.0002087459,0.0001193502,0.0002322991,0.001078538,0.0001143061,0.0009790275,0.000001196768,0.0001770738,0.000004431941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005644213,"about_ca_system_score_gemma":0.0002777214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006320967,"about_ca_topic_score_gemma":0.0006209337,"domain_scores_codex":[0.9960288,0.0002177594,0.002289178,0.0002557397,0.001001931,0.0002066364],"domain_scores_gemma":[0.9974446,0.001019169,0.0008738624,0.0001429358,0.0004442408,0.00007524098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005769316,0.00002455075,0.002442387,0.00002153512,0.00006290449,0.000280175,0.003211862,0.9613606,0.02129325,0.0005549049,0.00005137113,0.01011954],"study_design_scores_gemma":[0.004720983,0.001663708,0.6273041,0.003060854,0.001041697,0.0001514003,0.02134245,0.01506471,0.08005136,0.2423328,0.002153413,0.001112532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8728387,0.001465145,0.1243211,0.0005374097,0.0006341055,0.0001587351,0.00002555673,0.00001198714,0.00000723536],"genre_scores_gemma":[0.971543,0.00126378,0.02704141,0.00002182443,0.00008270962,0.000005268353,0.00001394649,0.00001113319,0.00001695662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9462959,"threshold_uncertainty_score":0.4866959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05311986818788987,"score_gpt":0.3473231225829956,"score_spread":0.2942032543951058,"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."}}