{"id":"W4388105650","doi":"10.3390/atmos14111632","title":"Mobile Laboratory Investigations of Industrial Point Source Emissions during the MOOSE Field Campaign","year":2023,"lang":"en","type":"article","venue":"Atmosphere","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks","funders":"Environment and Climate Change Canada; U.S. Environmental Protection Agency","keywords":"Environmental science; Trace gas; Oil refinery; Air quality index; Point source; Meteorology; Waste management; Engineering; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001754276,0.0001882273,0.000175289,0.000625013,0.0003381815,0.0003991817,0.0002123738,0.0002129868,0.001126042],"category_scores_gemma":[0.0003007344,0.00007006981,0.0001148483,0.0004749948,0.0001354663,0.0002277072,0.0003221016,0.0002415978,0.0003139378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002108953,"about_ca_system_score_gemma":0.0002556276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02263594,"about_ca_topic_score_gemma":0.06570572,"domain_scores_codex":[0.999864,0.00001574816,0.000004136379,0.00004240923,0.00004194354,0.00003169339],"domain_scores_gemma":[0.9998109,0.00002944508,0.00002987314,0.00002272225,0.00007656572,0.00003053103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005755495,0.0005197269,0.8719354,0.0001139961,0.0002554927,0.0008295812,0.001005931,0.00406546,0.07460576,0.0006606726,0.004404444,0.04102789],"study_design_scores_gemma":[0.00003519903,0.0003019481,0.9667294,0.00002694878,0.00004838782,0.0001943892,0.001046745,0.008091928,0.01219348,0.0001863229,0.01112465,0.0000205657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939956,0.00005897765,0.000674405,0.0000323289,0.000003911798,0.00002574524,0.00243014,0.00007824582,0.002700676],"genre_scores_gemma":[0.991848,0.00009340786,0.001560851,0.0000420426,0.00001123387,0.00003192959,0.004714041,0.00001999647,0.001678459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02263594,"threshold_uncertainty_score":0.04500836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466345531162218,"score_gpt":0.2125253585118776,"score_spread":0.1978619032002554,"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."}}