{"id":"W2135832014","doi":"10.5194/amt-7-3399-2014","title":"Verification and application of the extended spectral deconvolution algorithm (SDA+) methodology to estimate aerosol fine and coarse mode extinction coefficients in the marine boundary layer","year":2014,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Climate Program Office; Office of Naval Research; National Oceanic and Atmospheric Administration; National Aeronautics and Space Administration","keywords":"AERONET; Aerosol; Nephelometer; Deconvolution; Extinction (optical mineralogy); Remote sensing; Environmental science; Sun photometer; Single-scattering albedo; Algorithm; Mode (computer interface); Angstrom exponent; Meteorology; Scattering; Computer science; Physics; Optics; Light scattering; 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":[],"consensus_categories":[],"category_scores_codex":[0.00168261,0.0001579482,0.0001807351,0.000001099664,0.0001634961,0.00002268396,0.000221027,0.00007778485,0.00003306946],"category_scores_gemma":[0.0001110091,0.0001070829,0.00002975424,0.000295123,0.0002210108,0.00008583738,0.0001555642,0.0001181026,0.000002280824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001560051,"about_ca_system_score_gemma":0.00001144187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009391928,"about_ca_topic_score_gemma":0.0007441114,"domain_scores_codex":[0.9984126,0.0003121579,0.0003051158,0.0003549621,0.0004127312,0.0002024433],"domain_scores_gemma":[0.9993285,0.00005330946,0.0001686386,0.0003737922,0.00003057302,0.00004517437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000524133,0.0001778072,0.04101769,0.00001805294,0.000009053017,2.670454e-7,0.0004745845,0.0004756764,0.09056979,0.0004539002,0.0002275544,0.8665232],"study_design_scores_gemma":[0.0005933329,0.000530808,0.7535401,0.00004074208,0.00007212852,0.00002482312,0.0001650475,0.1867534,0.0458806,0.007867403,0.004148008,0.0003835863],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4156233,0.00002975499,0.582938,0.000271311,0.00003566056,0.0006745136,7.189654e-7,0.00004059078,0.0003861648],"genre_scores_gemma":[0.754865,0.00001822101,0.2447422,0.0001522067,0.00001659659,0.0001746535,0.000002076286,0.00001039189,0.00001869371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8661396,"threshold_uncertainty_score":0.4366715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099464815177335,"score_gpt":0.2814264542649774,"score_spread":0.260431806113204,"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."}}