{"id":"W3093123776","doi":"10.3390/atmos11101111","title":"Impacts of Regional Transport and Meteorology on Ground-Level Ozone in Windsor, Canada","year":2020,"lang":"en","type":"article","venue":"Atmosphere","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ground Level Ozone; Windsor; Environmental science; Air mass (solar energy); Ozone; Atmospheric sciences; Percentile; Meteorology; Climatology; Geography; Geology; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005769796,0.0001187636,0.0002128748,3.428199e-7,0.00003309657,0.000004182051,0.0001144597,0.00006867797,0.001389607],"category_scores_gemma":[0.00002039766,0.000102924,0.00002573489,0.0001507427,0.00007264699,0.00006602785,0.000004151308,0.0001376848,0.000004721148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005721418,"about_ca_system_score_gemma":0.0002120079,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5153269,"about_ca_topic_score_gemma":0.6800866,"domain_scores_codex":[0.9991937,0.00002082403,0.000194062,0.0002167402,0.0001672978,0.0002073506],"domain_scores_gemma":[0.9995749,0.00009495417,0.00006211344,0.00008699323,0.00001226335,0.0001687848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001867349,0.00001235398,0.9933822,0.00004617384,0.00001911844,0.00008324619,0.000244671,0.002071535,0.000233227,0.0000355533,0.0009040832,0.002781132],"study_design_scores_gemma":[0.0005126976,0.0001733501,0.995169,0.00001975995,0.000008226629,0.00001351012,0.0002962344,0.0007305708,0.0003392202,0.00007234693,0.002529742,0.0001352713],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954982,0.0004562499,0.00001302027,0.001708044,0.00003850495,0.0000639804,0.00005599262,0.000008225928,0.002157786],"genre_scores_gemma":[0.9976568,0.00004886349,0.0005803981,0.001537877,0.00004796005,4.103201e-7,0.00004329136,0.000003040576,0.00008133166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1647598,"threshold_uncertainty_score":0.9995233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02143897548179004,"score_gpt":0.1974736549955199,"score_spread":0.1760346795137299,"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."}}