{"id":"W4407735490","doi":"10.3233/978-1-58603-899-1-148","title":"The Trade-offs in Rail-Truck Intermodal Transportation of Hazardous Materials: an Illustrative Case Study","year":2008,"lang":"en","type":"book-chapter","venue":"NATO science for peace and security series. Sub-series E, Human and societal dynamics","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Truck; Hazardous waste; Transport engineering; Environmental science; Engineering; Automotive engineering; Waste management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.003079742,0.0005344365,0.001095611,0.0003473324,0.002421746,0.0006755851,0.0008706907,0.0003852712,0.00002354408],"category_scores_gemma":[0.0001547571,0.0004000413,0.0002986625,0.0004176335,0.005711582,0.00187604,0.0001182387,0.0004983408,7.986482e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000125655,"about_ca_system_score_gemma":0.0003213169,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003879147,"about_ca_topic_score_gemma":0.07629456,"domain_scores_codex":[0.9953143,0.0001382034,0.001476218,0.001154378,0.001416214,0.0005006723],"domain_scores_gemma":[0.9975818,0.0003048364,0.0007697949,0.0006244367,0.0004888013,0.0002302806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.001890931,0.0007255812,0.002513682,0.0002975336,0.0004629919,0.001397624,0.5647185,0.0000838185,0.0008786594,0.3838906,0.0007078249,0.04243224],"study_design_scores_gemma":[0.003792381,0.007020373,0.01194956,0.000176296,0.0005366699,0.001631679,0.6579056,0.007284923,0.0004295079,0.2973616,0.009166799,0.002744589],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995379,0.0006855369,0.00003841905,0.0003045339,0.0002517332,0.001003689,0.0009178804,0.00002667902,0.001392536],"genre_scores_gemma":[0.9893891,0.004734011,0.00007865506,0.00002423024,0.00005434718,0.00002948011,0.0001104912,0.00003143637,0.005548233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09318712,"threshold_uncertainty_score":0.9998451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04188926829659226,"score_gpt":0.3334718325794154,"score_spread":0.2915825642828231,"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."}}