{"id":"W3107587298","doi":"10.1175/bams-d-19-0227.1","title":"The Shortwave Spectral Radiometer for Atmospheric Science: Capabilities and Applications from the ARM User Facility","year":2020,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"U.S. Department of Energy","keywords":"Shortwave; Environmental science; Remote sensing; Aerosol; Shortwave radiation; Radiometer; Cloud computing; Meteorology; Radiative transfer; Radiation; Computer science; Physics; Optics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006540713,0.0001614369,0.0002451304,1.039093e-7,0.0009913596,0.00005695828,0.00101929,0.00003969538,0.0007316899],"category_scores_gemma":[0.0002768157,0.00006938509,0.0002898289,0.0004114208,0.01010777,0.00002018353,0.000593885,0.0002019809,0.00002087319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007214525,"about_ca_system_score_gemma":0.00002001057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006941757,"about_ca_topic_score_gemma":0.000008918866,"domain_scores_codex":[0.9984228,0.0001200948,0.0002484761,0.0004560775,0.0003837064,0.000368825],"domain_scores_gemma":[0.9982612,0.0009567586,0.0002052897,0.0004378266,0.00001871785,0.0001202407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006497205,0.0005075266,0.6283897,0.00003011794,0.0003977605,6.030472e-7,0.007272935,0.002124422,0.0415259,0.003938998,0.1586099,0.1565524],"study_design_scores_gemma":[0.0002900896,0.0004973452,0.4473884,0.000001642111,0.00008489928,0.00000157245,0.006851151,0.001481147,0.000895662,0.00251444,0.5397367,0.0002569073],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690131,0.0001677879,0.003107513,0.02636914,0.00002928039,0.0007191334,0.00005600859,0.00002807262,0.0005099511],"genre_scores_gemma":[0.9775748,0.000112622,0.01501983,0.006870343,0.00008546698,0.0001694018,0.000001270036,0.000006953684,0.0001593582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3811268,"threshold_uncertainty_score":0.9925861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041641771077981,"score_gpt":0.2182608424449894,"score_spread":0.2078444247342096,"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."}}