{"id":"W2031773927","doi":"10.1097/00001648-200407000-00531","title":"PREDICTING SPATIAL VARIABILITY OF AMBIENT NITROGEN DIOXIDE IN MONTRÉAL, CANADA, WITH A LAND USE REGRESSION MODEL","year":2004,"lang":"en","type":"article","venue":"Epidemiology","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Health Canada","funders":"","keywords":"Linear regression; Environmental science; Regression analysis; Nitrogen dioxide; Simple linear regression; Statistics; Population; Regression; Coefficient of determination; Atmospheric sciences; Hydrology (agriculture); Meteorology; Geography; Mathematics; Environmental health; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007835471,0.0009068474,0.0003682602,0.0009126429,0.000453276,0.0008265132,0.001299236,0.0003973118,0.001682437],"category_scores_gemma":[0.001530771,0.0002893283,0.0006597601,0.0009499526,0.0002669702,0.0002704812,0.0004365661,0.0004031613,0.0004095634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006214919,"about_ca_system_score_gemma":0.005483379,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9350025,"about_ca_topic_score_gemma":0.8933573,"domain_scores_codex":[0.9997205,0.00006454599,0.0000128371,0.00008922855,0.00005185343,0.00006097121],"domain_scores_gemma":[0.999361,0.0001896709,0.0000650408,0.00002501303,0.0003163954,0.00004294043],"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":[0.0001716352,0.0001648922,0.226506,0.00004550935,0.0002766972,0.000111083,0.00008832453,0.7402864,0.001443357,0.0006280969,0.004108543,0.02616947],"study_design_scores_gemma":[0.000009752825,0.00001817266,0.03063549,0.000005065188,0.00001901322,0.000007075796,0.00002868489,0.9684469,0.0001590536,0.00007303738,0.0005876111,0.00001026092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515801,0.0003740679,0.03601313,0.0004150143,0.00004409308,0.0001610546,0.007531441,0.0007297822,0.00315123],"genre_scores_gemma":[0.9806497,0.0001492515,0.01116368,0.00003884902,0.00001117713,0.00009986188,0.003450525,0.00004407275,0.004392838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06499749,"threshold_uncertainty_score":0.1307605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04781424174803132,"score_gpt":0.2921549233934019,"score_spread":0.2443406816453706,"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."}}