{"id":"W2811322387","doi":"10.1016/j.envres.2018.06.036","title":"Spatial modeling of daily concentrations of ground-level ozone in Montreal, Canada: A comparison of geostatistical approaches","year":2018,"lang":"en","type":"article","venue":"Environmental Research","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de Santé Publique du Québec; Centre Hospitalier de l’Université de Montréal; Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Ground Level Ozone; Environmental science; Kriging; Mean squared error; Ground level; Ozone; Air pollution; Atmospheric sciences; Meteorology; Geography; Statistics; Mathematics; Ecology","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":[0.0007933571,0.0005752356,0.000381249,0.0006950334,0.000951034,0.001196247,0.001450658,0.0005503406,0.001092075],"category_scores_gemma":[0.002301573,0.0004114445,0.00079641,0.0009830249,0.0004366791,0.0003564021,0.0005071916,0.0003962833,0.0001075001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008010721,"about_ca_system_score_gemma":0.01460253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9838347,"about_ca_topic_score_gemma":0.9694421,"domain_scores_codex":[0.9997292,0.00007367181,0.00001547902,0.00006830021,0.000051694,0.00006158024],"domain_scores_gemma":[0.9993236,0.0002926352,0.00006583823,0.0000338035,0.0002393394,0.00004480752],"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":[0.00005412144,0.00004408636,0.0227448,0.00002235473,0.0001007357,0.00002860035,0.00005643395,0.9681373,0.0003157362,0.001060558,0.0004552917,0.006979997],"study_design_scores_gemma":[0.00001311647,0.00001019819,0.007668707,0.000004069203,0.00002441091,0.000004638046,0.00006205725,0.9916903,0.0001299752,0.0001623645,0.0002200339,0.00001012374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707239,0.0005264746,0.02390499,0.0006540847,0.00002864557,0.00005409563,0.001721616,0.0003422662,0.002043807],"genre_scores_gemma":[0.9892032,0.0003025186,0.00786813,0.00003682575,0.000009676949,0.00003065109,0.0008429959,0.00004175049,0.001664222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01616526,"threshold_uncertainty_score":0.0581221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2770953651680124,"score_gpt":0.3910531361815842,"score_spread":0.1139577710135718,"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."}}