{"id":"W2937970224","doi":"10.5194/acp-2019-289","title":"Towards continuous monitoring of aerosol hygroscopicity by Raman lidar measurements at the EARLINET station of Payerne","year":2019,"lang":"en","type":"article","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"European Commission; Université de Lille; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Bundesamt für Umwelt; Ministerio de Economía y Competitividad; National Science Foundation","keywords":"Radiosonde; Aerosol; Lidar; Environmental science; Remote sensing; Altitude (triangle); Backscatter (email); Meteorology; Atmospheric sciences; Relative humidity; Geography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006762649,0.0003172634,0.0002643969,0.0006989847,0.0004006584,0.0004744127,0.0004812133,0.0004562381,0.0008932481],"category_scores_gemma":[0.0004311346,0.0001562444,0.0001511906,0.0003214206,0.0001595091,0.0004527612,0.000375874,0.0003167614,0.0002517776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001892262,"about_ca_system_score_gemma":0.0002607415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01035449,"about_ca_topic_score_gemma":0.02026522,"domain_scores_codex":[0.9995751,0.00008513715,0.00001652997,0.0001131084,0.0001636309,0.00004655527],"domain_scores_gemma":[0.999755,0.00005475859,0.00003104915,0.0000237191,0.0001106086,0.00002485806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008562107,0.0002980412,0.4265938,0.000139005,0.00009012051,0.0004907201,0.0009981018,0.003314974,0.5117114,0.0001683011,0.0003970358,0.0549424],"study_design_scores_gemma":[0.00007667026,0.0008430275,0.8968743,0.00002957758,0.00006552079,0.0003126842,0.0005924164,0.02368066,0.07463185,0.00005886265,0.002793254,0.00004119942],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99762,0.0000985482,0.001432815,0.000009844623,0.000006428326,0.00001236647,0.0001555327,0.00004151605,0.0006228198],"genre_scores_gemma":[0.995174,0.00003734144,0.003875957,0.000009174464,0.000008099733,0.00001801686,0.0003196285,0.00000670902,0.0005510803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01035449,"threshold_uncertainty_score":0.02058846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386028944908505,"score_gpt":0.2354350387426964,"score_spread":0.2215747492936113,"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."}}