{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003060249,0.000108215,0.000247368,0.0001982334,0.00002960505,0.00001242128,0.0001000237,0.00004651408,0.00009883777],"category_scores_gemma":[0.0001031439,0.00009834817,0.00007550252,0.001612622,0.00002136082,0.00005884284,0.00003584528,0.0003318183,1.75853e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001540675,"about_ca_system_score_gemma":0.001048023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8088697,"about_ca_topic_score_gemma":0.6408266,"domain_scores_codex":[0.9990955,0.00004680684,0.0002800878,0.0001738815,0.0001486648,0.0002550489],"domain_scores_gemma":[0.9995302,0.00006761574,0.00001297562,0.0002239708,0.00007553845,0.00008971281],"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":[0.000006654346,0.00001089337,0.5237333,0.0006269048,0.0001198116,0.00002982469,0.0007025864,0.4540375,0.0002991823,0.0001239628,0.00002916524,0.02028018],"study_design_scores_gemma":[0.000044219,0.000007496402,0.2333315,0.00001833188,0.00005845379,3.321965e-7,0.0003788919,0.7630011,0.0005765325,0.0001440603,0.002349132,0.00008988411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974099,0.0009653289,0.00004109682,0.0003045446,0.00008932028,0.00008748693,0.00001882173,0.00008933695,0.00099413],"genre_scores_gemma":[0.9997682,0.0000445701,0.00001346112,0.000005033742,0.00001213999,0.000008952887,0.00001158698,0.00001197956,0.000124071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3089637,"threshold_uncertainty_score":0.4028812,"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."}}