{"id":"W1995142565","doi":"10.3141/2011-14","title":"Global and Country Inventory of Road Passenger and Freight Transportation","year":2007,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Truck; Particulates; Emission inventory; Diesel fuel; Road transport; Environmental science; Gasoline; China; Transport engineering; Business; Economy; Natural resource economics; Air quality index; Environmental protection; Geography; Engineering; Economics; Meteorology; Waste management; Automotive engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.003440458,0.000209893,0.0003725821,0.0005136533,0.0002824392,0.0000498201,0.0003695272,0.0002105306,0.00009854191],"category_scores_gemma":[0.00003973854,0.0001655817,0.00013525,0.001381407,0.000532296,0.0005553596,0.000002624487,0.001101396,0.000001763273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001288813,"about_ca_system_score_gemma":0.0001819475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002818125,"about_ca_topic_score_gemma":0.03091528,"domain_scores_codex":[0.9958574,0.0002018932,0.001187706,0.0002388465,0.001899711,0.0006144546],"domain_scores_gemma":[0.9976342,0.0003066567,0.0002125077,0.0002502296,0.001201382,0.0003949768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009068202,0.0001270208,0.9492871,0.0009661444,0.0001789184,0.00009172889,0.003052798,0.002169028,0.008373491,0.002384505,0.002357193,0.03010525],"study_design_scores_gemma":[0.001067927,0.0002498114,0.9861376,0.0003361256,0.00004068317,0.000001301075,0.001180202,0.0007649169,0.001782566,0.0009027784,0.007376907,0.0001592069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960489,0.001400512,0.001141215,0.0002915622,0.0003021226,0.0004108744,0.000110672,0.00002727724,0.0002668556],"genre_scores_gemma":[0.9952989,0.003596626,0.0008268472,0.00001445042,0.0001142736,0.00001085976,0.00001787427,0.00003403008,0.0000861715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03685047,"threshold_uncertainty_score":0.986768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04070981721333041,"score_gpt":0.3370324940481089,"score_spread":0.2963226768347785,"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."}}