{"id":"W4409686135","doi":"10.3390/su17093762","title":"Reducing Carbon Emissions from Transport Sector: Experience and Policy Design Considerations","year":2025,"lang":"en","type":"article","venue":"Sustainability","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; Carbon fibers; Environmental economics; Business; Natural resource economics; Environmental science; Environmental planning; Economics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006036302,0.0004258757,0.0004306256,0.001109886,0.0006574898,0.003048303,0.0009723035,0.001086493,0.002677462],"category_scores_gemma":[0.006839368,0.0001618282,0.0005605881,0.003220106,0.0007434028,0.003562248,0.001055583,0.001448086,0.0003089115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004754636,"about_ca_system_score_gemma":0.008264349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02695656,"about_ca_topic_score_gemma":0.01879891,"domain_scores_codex":[0.9975464,0.001177334,0.0001431827,0.0001450046,0.000577412,0.0004106898],"domain_scores_gemma":[0.995289,0.002116591,0.0003527636,0.0001287754,0.001864456,0.000248465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005449786,0.0006547712,0.02315413,0.0166793,0.00027331,0.001990081,0.009511001,0.02769736,0.006082125,0.1232693,0.02907993,0.7610638],"study_design_scores_gemma":[0.00009534627,0.001600705,0.02884163,0.01489133,0.0003979602,0.00111127,0.02913558,0.007148097,0.0114312,0.02419796,0.8809987,0.0001502897],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.332472,0.3083926,0.01805855,0.09772217,0.0006791122,0.0003586248,0.001061201,0.0001285294,0.2411273],"genre_scores_gemma":[0.6612567,0.3188529,0.007037127,0.003821042,0.0002277809,0.0001277151,0.0004842119,0.00004836473,0.008144144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02695656,"threshold_uncertainty_score":0.0535993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479071131798979,"score_gpt":0.2777320032133341,"score_spread":0.2629412918953443,"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."}}