{"id":"W2751119601","doi":"","title":"The quantification of mobile source contributions to fine particulate matter in the Greater Toronto Area","year":2001,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Particulates; Environmental science; Geography; Chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006801659,0.0001213038,0.0001524193,0.0000112296,0.0002011323,0.0000310998,0.0002376985,0.0001044718,0.001840393],"category_scores_gemma":[0.00007577775,0.00007180603,0.00004241584,0.0001401745,0.00005025432,0.00006276016,0.00002054484,0.0001290933,0.0005316827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002172651,"about_ca_system_score_gemma":0.00001891042,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.008973052,"about_ca_topic_score_gemma":0.04562797,"domain_scores_codex":[0.998834,0.0001514734,0.0002928475,0.0001835145,0.000255318,0.000282918],"domain_scores_gemma":[0.9992213,0.0001324921,0.0001619646,0.00039761,0.00001896232,0.00006765605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001100196,0.0007992215,0.06036065,0.0003127569,0.00007619133,0.00001023224,0.3862439,0.02005623,0.007018179,0.001478148,0.493325,0.02921934],"study_design_scores_gemma":[0.0003295451,0.0001704826,0.7521048,0.000125892,0.00004984868,0.000004032974,0.02370514,0.0005747904,0.002550196,0.0003702145,0.2197159,0.0002991668],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9751839,0.0002090021,0.0004731927,0.01187829,0.0001243499,0.001086804,0.00002054267,0.00001442291,0.01100949],"genre_scores_gemma":[0.9613115,0.0000601778,0.00003042364,0.0008641836,0.00003119226,0.0002314615,0.0001273052,0.00001228937,0.0373315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6917441,"threshold_uncertainty_score":0.9990721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03438500782184888,"score_gpt":0.3756566106149087,"score_spread":0.3412716027930598,"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."}}