{"id":"W2003688041","doi":"10.1016/j.earscirev.2014.11.001","title":"Aerosol remote sensing in polar regions","year":2014,"lang":"en","type":"article","venue":"Earth-Science Reviews","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":162,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Institut du Savoir Montfort; Université de Sherbrooke","funders":"National Oceanic and Atmospheric Administration; U.S. Department of Energy","keywords":"AERONET; Aerosol; Environmental science; Angstrom exponent; Sun photometer; Arctic; Atmospheric sciences; Climatology; Polar night; Oceanography; Geography; Geology; Meteorology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001939352,0.0001634764,0.0002853893,0.000004689221,0.0002795754,0.00005770456,0.0004275719,0.00004768389,0.0005188638],"category_scores_gemma":[0.0003474737,0.0001295972,0.00008230948,0.001124077,0.0006475066,0.0003206934,0.0002203689,0.000184514,0.002217694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009136826,"about_ca_system_score_gemma":0.0000243847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005385279,"about_ca_topic_score_gemma":0.0004852713,"domain_scores_codex":[0.9980416,0.0001381894,0.0003654676,0.0005146718,0.0004016228,0.0005384039],"domain_scores_gemma":[0.9990453,0.00003182917,0.0001354084,0.0005872261,0.000006938515,0.0001933084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002662857,0.00002708475,0.002892787,0.0000146966,7.575135e-7,0.000007694074,0.0005308409,0.0001709321,0.2636939,0.0003153928,0.00160891,0.7307343],"study_design_scores_gemma":[0.0003099816,0.0001199701,0.01731972,0.0002570158,0.00001068702,0.00005792454,0.00007909466,0.01442564,0.01085272,0.0009921836,0.9549518,0.000623238],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3156719,0.002223576,0.5184056,0.002345994,0.0007078157,0.001399022,0.000001252983,0.0001475496,0.1590973],"genre_scores_gemma":[0.6351724,0.002451985,0.3560215,0.002541313,0.0001478787,0.000002842224,0.000001237944,0.00002928611,0.003631629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9533429,"threshold_uncertainty_score":0.9985592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01697063926479219,"score_gpt":0.250911482127045,"score_spread":0.2339408428622528,"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."}}