{"id":"W4240981817","doi":"10.5194/amt-2019-182","title":"Analysis of Global Three-Dimensional Aerosol Structure with Spectral Radiance Matching","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Radiance; Nadir; Remote sensing; Lidar; Aerosol; Environmental science; Track (disk drive); Pixel; Meteorology; Geology; Satellite; Computer science; Geography; Optics; 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":[0.0005980671,0.0003241625,0.000239635,0.001099214,0.0001468604,0.0004157478,0.0003439437,0.0002557871,0.0007065574],"category_scores_gemma":[0.001115844,0.0001435625,0.0006009592,0.0008134317,0.000137122,0.0004012396,0.0004733117,0.0001798065,0.0002898047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002533022,"about_ca_system_score_gemma":0.0003166119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003278779,"about_ca_topic_score_gemma":0.002451924,"domain_scores_codex":[0.9998304,0.00003633508,0.000008874978,0.00004843271,0.0000564032,0.00001964422],"domain_scores_gemma":[0.9996505,0.00007334425,0.0000564566,0.0001106795,0.00009204925,0.00001699067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004943649,0.0002864187,0.102692,0.000144912,0.0004518687,0.0002656066,0.0001620165,0.395825,0.08867126,0.004714666,0.001724551,0.4045673],"study_design_scores_gemma":[0.00001637554,0.00003805183,0.0339784,0.000004465595,0.00002549641,0.00004745962,0.00003132955,0.9539393,0.01004195,0.00106422,0.000800819,0.00001219476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7145631,0.0001466784,0.2805469,0.00005940699,0.00001983543,0.00007140017,0.001024707,0.001680418,0.001887466],"genre_scores_gemma":[0.8828095,0.00003982436,0.1154348,0.00001450722,0.000008945202,0.00002175087,0.001160605,0.0001130533,0.000397099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003278779,"threshold_uncertainty_score":0.006519437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005725789815775107,"score_gpt":0.214794089131166,"score_spread":0.2090682993153909,"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."}}