{"id":"W2766766087","doi":"10.5194/acp-18-5499-2018","title":"Using spectral methods to obtain particle size information from optical data: applications to measurements from CARES 2010","year":2018,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Biological and Environmental Research; U.S. Department of Energy","keywords":"Deconvolution; Effective radius; Single-scattering albedo; Wavelength; Radiative transfer; Aerosol; Particle-size distribution; Particle size; Scattering; Absorption (acoustics); Extinction (optical mineralogy); Remote sensing; Optics; AERONET; Particle (ecology); Computational physics; Physics; Chemistry; Meteorology; Geology; Astrophysics","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":[0.001035753,0.0004919228,0.0002849759,0.002473485,0.0005429972,0.0004633784,0.0005929928,0.0004217204,0.0006427667],"category_scores_gemma":[0.002386217,0.000272956,0.0004870814,0.001707983,0.0002816546,0.0004237508,0.0005035098,0.0004419441,0.000278136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007208881,"about_ca_system_score_gemma":0.0006065773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02292513,"about_ca_topic_score_gemma":0.05018352,"domain_scores_codex":[0.9994362,0.00007286329,0.00003823723,0.0001005131,0.0003225133,0.00002962967],"domain_scores_gemma":[0.9991736,0.0002503561,0.0001136384,0.0001075564,0.0003241934,0.00003059916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004239953,0.0007794682,0.2859709,0.0007933061,0.000438868,0.0006904745,0.001686488,0.03234418,0.2663214,0.001587433,0.005771141,0.4031924],"study_design_scores_gemma":[0.0001476844,0.0002728789,0.5577165,0.00007249933,0.0001476341,0.0008428429,0.0008561827,0.2454111,0.182514,0.002058678,0.009804199,0.0001557236],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9336146,0.0004888329,0.05683484,0.0001800845,0.0000415835,0.0003190335,0.002420821,0.001061683,0.00503861],"genre_scores_gemma":[0.8354816,0.0002667476,0.1607805,0.00008876131,0.00002097404,0.0001702545,0.002167599,0.0001085771,0.0009149975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02292513,"threshold_uncertainty_score":0.04558343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06036724684427493,"score_gpt":0.3096806533693697,"score_spread":0.2493134065250947,"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."}}