{"id":"W2460924004","doi":"10.1016/j.atmosenv.2016.06.053","title":"Photochemical model evaluation of the ground-level ozone impacts on ambient air quality and vegetation health in the Alberta oil sands region: Using present and future emission scenarios","year":2016,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of Alberta; Cumulative Environmental Management Association","funders":"Egg Farmers of Canada; National Center for Atmospheric Research; U.S. Environmental Protection Agency","keywords":"CMAQ; Ozone; Environmental science; Air quality index; Ground Level Ozone; Vegetation (pathology); Cumulative effects; Atmospheric sciences; Hydrology (agriculture); Environmental engineering; Meteorology; Engineering; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000870924,0.0002435162,0.0002251617,0.000001533657,0.0001876983,0.00001089507,0.0002018823,0.0001080057,0.00005560748],"category_scores_gemma":[0.00001963255,0.0001302817,0.00005767013,0.0001125586,0.0004103642,0.0001581306,0.0002442306,0.0001456787,0.00000308846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017482,"about_ca_system_score_gemma":0.00002491075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001226763,"about_ca_topic_score_gemma":0.00007309468,"domain_scores_codex":[0.9975597,0.0003564991,0.0004250852,0.0004685736,0.0008839168,0.0003062428],"domain_scores_gemma":[0.9989831,0.00009193899,0.0003044454,0.0004947187,0.000002814336,0.0001229108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002332244,0.000944654,0.2151457,0.00007825377,0.00003924148,0.000001676117,0.006366938,0.6108283,0.01757238,0.0001105189,0.0002423548,0.1484368],"study_design_scores_gemma":[0.001356054,0.0001431396,0.7218981,0.0001109206,0.00004333582,0.0000170029,0.0005125329,0.2745063,0.0001622298,0.0004535299,0.0005617437,0.0002351182],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906506,0.0002888723,0.002390818,0.005893941,0.00004393248,0.000516998,0.000001872683,0.000004834065,0.0002081565],"genre_scores_gemma":[0.9942271,0.001009814,0.003612612,0.0008528717,0.00004164667,0.00004646225,0.000002429125,0.00001940911,0.0001876422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5067524,"threshold_uncertainty_score":0.5312731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0384866159501515,"score_gpt":0.2798162232077124,"score_spread":0.2413296072575609,"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."}}