{"id":"W2980259060","doi":"10.5539/enrr.v9n4p9","title":"Tropospheric NO2 Monitoring Using the Multi-Axis Differential Optical Absorption Spectroscopy in Urban Area","year":2019,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro","keywords":"Differential optical absorption spectroscopy; Trace gas; Troposphere; Environmental science; Absorption (acoustics); Atmospheric sciences; Remote sensing; Atmosphere (unit); Absorption spectroscopy; Ultraviolet; Meteorology; Optics; Physics; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009082707,0.0001563684,0.0001376381,0.0003848647,0.0001665961,0.0002055263,0.0001645844,0.0001360768,0.0001521779],"category_scores_gemma":[0.00009597979,0.00007688891,0.0001183606,0.0004050427,0.00006528018,0.0001562534,0.0001257797,0.00007882691,0.00004909495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001518991,"about_ca_system_score_gemma":0.0001121473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008369936,"about_ca_topic_score_gemma":0.02474995,"domain_scores_codex":[0.9999214,0.00001160808,0.000002565825,0.00002914489,0.00002560886,0.000009553776],"domain_scores_gemma":[0.9999599,0.000006601529,0.000009758715,0.000004595881,0.00001519173,0.000003906274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003507454,0.0001373916,0.3670183,0.0002702428,0.0001326745,0.0003884757,0.0004039728,0.01036958,0.5359928,0.0003673921,0.0008589498,0.08370958],"study_design_scores_gemma":[0.0000132272,0.0001740945,0.8632181,0.00001453827,0.0000813901,0.0002183001,0.0003415189,0.03883445,0.09370314,0.0001908525,0.003180828,0.00002960003],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949459,0.0002233518,0.003058738,0.00001894307,0.000005660988,0.000007176553,0.0002981092,0.0000474246,0.001394649],"genre_scores_gemma":[0.9955918,0.00014145,0.003665315,0.000006627779,0.000003731445,0.000006564997,0.0002409204,0.000004723047,0.0003388147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008369936,"threshold_uncertainty_score":0.01664239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05035212089072862,"score_gpt":0.3177172810009825,"score_spread":0.2673651601102539,"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."}}