{"id":"W4404927918","doi":"10.3390/su162310526","title":"Towards Carbon Neutrality: Machine Learning Analysis of Vehicle Emissions in Canada","year":2024,"lang":"en","type":"article","venue":"Sustainability","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Carbon neutrality; Neutrality; Carbon fibers; Greenhouse gas; Environmental economics; Environmental science; Automotive engineering; Engineering; Computer science; Economics; Political science; Electrical engineering; Renewable energy; Law; Algorithm","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":[0.0009765094,0.0003770604,0.0002714769,0.001232477,0.0009772638,0.0009439551,0.000642627,0.0003025508,0.0006486839],"category_scores_gemma":[0.003044291,0.0001100972,0.0004743535,0.001979272,0.0005298082,0.0003724251,0.0003891095,0.0006277284,0.00008719706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02012581,"about_ca_system_score_gemma":0.02477623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9895005,"about_ca_topic_score_gemma":0.9873241,"domain_scores_codex":[0.9996073,0.00006079668,0.0000125826,0.00005443162,0.0001457958,0.0001190724],"domain_scores_gemma":[0.9990804,0.0001742638,0.00006217977,0.00002786235,0.0005950243,0.00006022246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002834666,0.0001884647,0.4730718,0.0001199099,0.0002103208,0.0003400842,0.0004247168,0.4500539,0.001564017,0.01043438,0.004465297,0.05884371],"study_design_scores_gemma":[0.00001526581,0.00004572988,0.269281,0.00003714815,0.00004943151,0.00003789221,0.001082349,0.7211832,0.00190752,0.002251769,0.004067597,0.00004107101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911276,0.0003644709,0.003595719,0.0005956407,0.00001001755,0.00003027205,0.001170225,0.00005334314,0.003052672],"genre_scores_gemma":[0.9956779,0.0002078791,0.001685986,0.0000269231,0.00000271013,0.000006580246,0.001095411,0.000007322839,0.00128937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02012581,"threshold_uncertainty_score":0.1460236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005904221419786656,"score_gpt":0.2339425984316766,"score_spread":0.22803837701189,"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."}}