{"id":"W2773202291","doi":"10.5194/amt-11-2553-2018","title":"Detection of carbon monoxide pollution from cities and wildfires on regional and urban scales: the benefit of CO column retrievals from SCIAMACHY 2.3 µm measurements under cloudy conditions","year":2018,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"SCIAMACHY; Environmental science; Sky; Meteorology; Shortwave; Column (typography); Carbon monoxide; Cloud computing; Troposphere; Pollution; Air pollution; Atmospheric sciences; Remote sensing; Geography; Computer science; Geology; Chemistry; Radiative transfer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005192162,0.0002606937,0.0002987878,0.000004308949,0.0002628756,0.00002363528,0.0002058647,0.0001444877,0.00009035628],"category_scores_gemma":[0.00003797817,0.0002186662,0.00006106824,0.000200782,0.001495036,0.0001342274,0.0001170213,0.0001318569,0.000002434315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004282378,"about_ca_system_score_gemma":0.00001379528,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.011642,"about_ca_topic_score_gemma":0.0006514615,"domain_scores_codex":[0.9977154,0.0001261805,0.000445872,0.0004423835,0.001039629,0.0002305386],"domain_scores_gemma":[0.999072,0.00006376434,0.0003554822,0.0003804435,0.00003906994,0.00008920951],"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":[0.0002278946,0.0002314274,0.4660735,0.00001362156,0.000192752,5.817316e-7,0.0007488271,0.000338105,0.5227398,0.00009487764,0.0003450824,0.008993546],"study_design_scores_gemma":[0.0003925831,0.0006500827,0.8626528,0.0001336496,0.0001174662,0.000001729644,0.0006461002,0.001449534,0.1290991,0.004347877,0.0002444481,0.000264536],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940534,0.0004212326,0.003924409,0.0001440085,0.00006459693,0.0005575144,0.00002474647,0.00007611285,0.0007339853],"genre_scores_gemma":[0.9931582,0.0002629647,0.006105844,0.0002870767,0.000061585,0.00005026599,0.000008416336,0.0000274072,0.00003823707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3965794,"threshold_uncertainty_score":0.9949396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380876724783487,"score_gpt":0.2286262558582804,"score_spread":0.2048174886104455,"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."}}