{"id":"W2124075705","doi":"10.1175/2009jtecha1191.1","title":"The Effects of Precipitation on Cloud Droplet Measurement Devices","year":2009,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"National Science Foundation","keywords":"Precipitation; Liquid water content; Environmental science; Spectrometer; Cloud computing; Atmospheric sciences; Volume (thermodynamics); Meteorology; Liquid water; Climatology; Geology; Physics; Computer science; Optics; Thermodynamics","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":[0.0003471858,0.0001164612,0.0002101886,8.624111e-7,0.0001270225,0.00001190662,0.0002683949,0.0001015933,0.00003065964],"category_scores_gemma":[0.0001807224,0.00007022652,0.00005960711,0.0002720891,0.0002071087,0.0000697116,0.00004466168,0.0001955278,0.000005699746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009291087,"about_ca_system_score_gemma":0.00001853819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003973822,"about_ca_topic_score_gemma":0.000004434685,"domain_scores_codex":[0.9989311,0.00003692351,0.0003532938,0.000119524,0.0003769374,0.0001822439],"domain_scores_gemma":[0.9992055,0.00008991325,0.0004563776,0.0001592098,0.0000389943,0.00004996904],"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":[0.0003095097,0.0004446171,0.05564641,0.00004014626,0.0001325797,0.00004119955,0.0005518538,0.0003220193,0.02557973,0.006706264,0.008922283,0.9013034],"study_design_scores_gemma":[0.002388346,0.01313141,0.9071806,0.0002958542,0.0002016799,0.0002101625,0.001589946,0.0008403424,0.01282685,0.02355705,0.03734818,0.0004295887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936093,0.002132683,0.001750538,0.001504952,0.0002516591,0.0001189489,1.024009e-7,0.00001619204,0.0006156332],"genre_scores_gemma":[0.9959872,0.0006720922,0.003029245,0.0001961761,0.00004228104,0.000001050655,3.195949e-8,0.000006253778,0.00006566247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9008738,"threshold_uncertainty_score":0.2863754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003594396476984071,"score_gpt":0.1970399313035632,"score_spread":0.1934455348265791,"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."}}