{"id":"W2059114617","doi":"10.1016/j.atmosenv.2008.07.023","title":"Estimating urban morphometry at the neighborhood scale for improvement in modeling long-term average air pollution concentrations","year":2008,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Noise Effects and Management","field":"Health Professions","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; University of British Columbia","funders":"British Columbia Centre for Disease Control","keywords":"Environmental science; Mean squared error; Air pollution; Scale (ratio); Pollution; Regression analysis; Meteorology; Thematic Mapper; Hydrology (agriculture); Statistics; Geography; Cartography; Satellite imagery; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004252865,0.0002174391,0.0002345089,0.000006875583,0.001297475,0.000006503029,0.0001643117,0.00009382594,0.0005608762],"category_scores_gemma":[0.0000245648,0.0001671647,0.00008930133,0.000125055,0.00007021621,0.0001143664,0.0002393243,0.0002438037,0.0001117532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108171,"about_ca_system_score_gemma":0.000051667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001772028,"about_ca_topic_score_gemma":0.00007909135,"domain_scores_codex":[0.9980362,0.0001327692,0.0005450639,0.0004007582,0.000286499,0.00059873],"domain_scores_gemma":[0.9991087,0.0001454346,0.000196834,0.0004362618,0.00001159974,0.0001011155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007884784,0.0003854068,0.2464488,0.0002133802,0.00006493654,0.00001453294,0.003570388,0.7381654,0.002052258,0.0002727254,0.003595211,0.005138038],"study_design_scores_gemma":[0.003388559,0.0003209639,0.2312395,0.0001756883,0.00007994896,0.000002703495,0.0006811395,0.7608021,0.0001434931,0.0001294734,0.002587831,0.0004485883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7489781,0.0002949031,0.2461516,0.001010016,0.0004108348,0.002609641,0.00001178481,0.0000408407,0.0004922976],"genre_scores_gemma":[0.984695,0.0001701183,0.008100281,0.00183986,0.0002314879,0.001279357,0.00005011295,0.00003835694,0.003595425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2380513,"threshold_uncertainty_score":0.9979259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02010174342206329,"score_gpt":0.2879231896994177,"score_spread":0.2678214462773544,"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."}}