{"id":"W2415482526","doi":"10.1021/acs.estlett.6b00182","title":"Satellite Remote Sensing of Air Quality in the Energy Golden Triangle in Northwest China","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology Letters","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Natural Science Foundation of China","keywords":"Ozone Monitoring Instrument; Troposphere; Air quality index; Satellite; Environmental science; Tropospheric ozone; China; Planetary boundary layer; Meteorology; Ozone; Atmospheric sciences; Pollutant; Remote sensing; Geography; Geology; Physics","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":[0.0001845048,0.0002144115,0.0002453847,0.0007312301,0.0003803656,0.0004405309,0.0002275438,0.0001891917,0.0002597975],"category_scores_gemma":[0.0001822488,0.0001170574,0.0001842242,0.001205328,0.0003000159,0.0002986071,0.000443464,0.00009367083,0.00004992962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009311133,"about_ca_system_score_gemma":0.0008382398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1886792,"about_ca_topic_score_gemma":0.2682907,"domain_scores_codex":[0.9998749,0.0000116911,0.000007435042,0.00002961216,0.00004954693,0.00002676037],"domain_scores_gemma":[0.9998599,0.00001244411,0.00003313396,0.00001190844,0.0000490449,0.00003353342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001781798,0.00006920107,0.9332151,0.00005098063,0.00007311209,0.0004864666,0.0007250422,0.007974921,0.03403231,0.0003060579,0.000493795,0.02239482],"study_design_scores_gemma":[0.00001146011,0.00002237057,0.9913955,0.000003373913,0.00001232752,0.00003176965,0.0003403965,0.006247213,0.001179792,0.0000405664,0.0007085011,0.000006659567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990938,0.00003474682,0.0001334123,0.00001129199,0.000001232303,0.000003730398,0.0001996106,0.000007521862,0.0005146997],"genre_scores_gemma":[0.9990684,0.0000340748,0.0002534646,0.000005698997,0.000001515721,0.000004408755,0.0003906485,0.000001581919,0.0002402111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1886792,"threshold_uncertainty_score":0.375162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445055276365153,"score_gpt":0.2596039552499977,"score_spread":0.2451534024863462,"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."}}