{"id":"W4251511484","doi":"10.5194/acp-2018-1009","title":"Characterization of nighttime formation of particulate organic nitrates based on high-resolution aerosol mass spectrometry in an urban atmosphere in China","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Particulates; Environmental chemistry; Aerosol; Atmosphere (unit); Nitrate; NOx; Chemistry; Ozone; Environmental science; Mass spectrometry; Meteorology; Combustion","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003060475,0.0004177211,0.0002692152,0.0006218757,0.0005852464,0.0004072782,0.0003150528,0.0003200797,0.0002542453],"category_scores_gemma":[0.0000998663,0.0001545637,0.0003188711,0.0005004311,0.0002200856,0.0003321236,0.0002441423,0.0001641783,0.00008641044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005148253,"about_ca_system_score_gemma":0.000605164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03101102,"about_ca_topic_score_gemma":0.05417367,"domain_scores_codex":[0.9998154,0.00001369387,0.00001054429,0.00007133483,0.00006615992,0.00002292985],"domain_scores_gemma":[0.9998772,0.000009054606,0.00002869316,0.00000641238,0.00006022889,0.00001836681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002324374,0.0001711272,0.7228233,0.0002691393,0.0002017568,0.000915229,0.0005684859,0.003220235,0.2513305,0.0001704432,0.0005967104,0.01950072],"study_design_scores_gemma":[0.00001586229,0.00008532049,0.964011,0.00000801331,0.00008037332,0.000123842,0.0002955136,0.01065837,0.02373016,0.00008334556,0.0008827868,0.00002540682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998689,0.0001118931,0.0006323102,0.00001700158,0.000006106338,0.000007280649,0.0001950642,0.00001230052,0.0003290531],"genre_scores_gemma":[0.9984246,0.00009171499,0.0007874891,0.00002276857,0.000006527549,0.000008238039,0.0002791405,0.000004586388,0.0003748073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03101102,"threshold_uncertainty_score":0.06166101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008184779875848659,"score_gpt":0.1960039087949811,"score_spread":0.1878191289191324,"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."}}