{"id":"W3003763400","doi":"10.1007/978-3-030-33566-3_9","title":"Remote Sensing of Arctic Atmospheric Aerosols","year":2020,"lang":"en","type":"book-chapter","venue":"Springer polar sciences","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; Université du Québec à Rimouski","funders":"","keywords":"Remote sensing; Aerosol; Radiometer; Environmental science; Arctic; Satellite; Instrumentation (computer programming); Lidar; Meteorology; The arctic; Geography; Geology; Oceanography; Computer science; Engineering; Aerospace engineering","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":[0.0002992772,0.0007968511,0.0004176248,0.001245002,0.0001591941,0.001403582,0.0006419879,0.0006914288,0.03964196],"category_scores_gemma":[0.0003785134,0.0003643093,0.0003332578,0.001909125,0.0001998084,0.001428797,0.0006419203,0.0008875436,0.02232184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00034441,"about_ca_system_score_gemma":0.0003193747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002858064,"about_ca_topic_score_gemma":0.006800098,"domain_scores_codex":[0.999866,0.00001167458,0.000004330765,0.00002252037,0.00008669215,0.000008789698],"domain_scores_gemma":[0.9998778,0.00006334762,0.000005540392,0.00001382685,0.00002935164,0.00001015193],"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":[0.00002339324,0.00003198154,0.0001643835,0.000373196,0.00001601953,0.00007849235,0.00005562179,0.002436046,0.006007848,0.01246059,0.2265936,0.7517589],"study_design_scores_gemma":[0.000002844289,0.00001279083,0.0008545027,0.0001744612,0.000005074233,0.0001499206,0.00002860452,0.002135973,0.00140377,0.006992733,0.9882296,0.000009721492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002709813,0.2117533,0.0778922,0.002669404,0.01153862,0.00007781127,0.002266009,0.001602071,0.6894907],"genre_scores_gemma":[0.01101441,0.1073646,0.02969246,0.001076249,0.003424417,0.00003967491,0.002311764,0.0007051672,0.8443713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03964196,"threshold_uncertainty_score":0.1326155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01690540286942031,"score_gpt":0.218836174884924,"score_spread":0.2019307720155037,"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."}}