{"id":"W7036485325","doi":"","title":"Characterizing and predicting ultrafine particle counts in Canadian homes, schools, and transportation environments : an exposure modeling study with implications in environmental epidemiology","year":2007,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Mediterranean and Iberian flora and fauna","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ultrafine particle; Particulates; Air pollution; Exposure assessment; Inhalation exposure; Air pollutants; Wind speed; Particulate pollution; Particle number","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":[0.001161635,0.0009976707,0.0004167272,0.0007166127,0.001676824,0.001253771,0.001462673,0.000785246,0.001373682],"category_scores_gemma":[0.002575198,0.0004169208,0.001201296,0.00121835,0.0003713286,0.0005596195,0.0006991436,0.0007051858,0.0001954429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01399228,"about_ca_system_score_gemma":0.01612978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9780748,"about_ca_topic_score_gemma":0.9742671,"domain_scores_codex":[0.9995408,0.0000976986,0.00001905149,0.0001417512,0.00008854341,0.000112185],"domain_scores_gemma":[0.9992406,0.000325836,0.00007204483,0.00004919538,0.0002310151,0.00008128649],"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":[0.000277753,0.001020899,0.7485432,0.0000953645,0.0004197262,0.0002443269,0.0007459245,0.2109608,0.001331229,0.001243184,0.002352737,0.03276483],"study_design_scores_gemma":[0.00005761609,0.0002005261,0.3292587,0.00002978628,0.0002518281,0.0000682481,0.001227062,0.6649596,0.0008977485,0.0005829739,0.002397017,0.0000688152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951703,0.0001528665,0.002464104,0.0002130912,0.000009556771,0.00004743362,0.0009416993,0.00004298401,0.0009578904],"genre_scores_gemma":[0.9899287,0.000308456,0.005964331,0.00006110842,0.00000744176,0.00004373436,0.001877166,0.00002226956,0.001786841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02192521,"threshold_uncertainty_score":0.1015216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02662949472165647,"score_gpt":0.2393170841559111,"score_spread":0.2126875894342546,"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."}}