{"id":"W7132864055","doi":"","title":"From Cameras to Concentrations: Estimating Black Carbon From Vehicles with Machine Learning and Computer Vision Techniques","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Feature (linguistics); Proxy (statistics); Deep learning; Traffic congestion; Variance (accounting); Machine vision","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003002861,0.0008194841,0.0005744521,0.001192055,0.0002603209,0.0007926493,0.0006592504,0.0006894075,0.0010563],"category_scores_gemma":[0.0009789524,0.0002948362,0.0005078265,0.001088894,0.0002048373,0.0007435299,0.0004116889,0.0008735649,0.0007198876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005819771,"about_ca_system_score_gemma":0.0005265478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009529666,"about_ca_topic_score_gemma":0.01173143,"domain_scores_codex":[0.999725,0.00003382918,0.00000913335,0.0001005593,0.00008447585,0.00004684937],"domain_scores_gemma":[0.9997833,0.00007012838,0.00003281858,0.00001990889,0.000079176,0.00001470617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002071465,0.0005999943,0.0188815,0.0001639699,0.0001752962,0.0001073412,0.000130301,0.2004038,0.04779421,0.001916053,0.005990814,0.7236296],"study_design_scores_gemma":[0.000005824481,0.00004952849,0.007799587,0.00001522857,0.00001622626,0.00003142059,0.00004773886,0.9751648,0.01415174,0.001294956,0.001405803,0.00001710187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3138245,0.00116871,0.6720272,0.0005246522,0.0001982497,0.0001487029,0.0009196053,0.003453767,0.007734767],"genre_scores_gemma":[0.7229305,0.000582915,0.2695909,0.0001723679,0.0001068542,0.0001143467,0.001380814,0.0001421614,0.004979125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009529666,"threshold_uncertainty_score":0.01894844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006922356718376179,"score_gpt":0.2852857614252364,"score_spread":0.2783634047068603,"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."}}