{"id":"W7006625018","doi":"","title":"Understanding Arctic aerosols : multi-station climatology of extensive- and intensive-parameter optical retrievals & evaluation of an advanced aerosol transport model versus the multi-station climatology","year":2022,"lang":"en","type":"dissertation","venue":"Knowledge UdeS (Institutional Deposit of the University of Sherbrooke)","topic":"Parasite Biology and Host Interactions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aerosol; Radiative forcing; Climate model; Forcing (mathematics); Earth's energy budget; Radiative transfer; Arctic; Optical depth; Climate change; Albedo (alchemy)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001297721,0.0006589763,0.0003235531,0.0005374188,0.0004114727,0.001224002,0.0004476889,0.0007297929,0.0008474519],"category_scores_gemma":[0.001058941,0.0001954379,0.0006913406,0.000554449,0.0001656714,0.0009496612,0.0004236301,0.0004654977,0.0002235958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008959775,"about_ca_system_score_gemma":0.0009356528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09579737,"about_ca_topic_score_gemma":0.06482558,"domain_scores_codex":[0.9997672,0.00006964599,0.00001326878,0.00007426032,0.00004163244,0.00003398099],"domain_scores_gemma":[0.9995567,0.000105351,0.00006256138,0.00005090921,0.0001611495,0.00006336878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004165627,0.0003883582,0.2999045,0.0001656297,0.0004873287,0.0001919254,0.0001901294,0.6459327,0.01500228,0.001817763,0.00163241,0.03387046],"study_design_scores_gemma":[0.00002962107,0.00006816884,0.0675591,0.00002373392,0.00007630108,0.00002004437,0.0001365597,0.9276491,0.002969963,0.000238579,0.001208741,0.00002018194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890827,0.0003215526,0.005689698,0.0003930381,0.00006220754,0.00004473514,0.001746909,0.0002612046,0.002398036],"genre_scores_gemma":[0.9918237,0.000122195,0.006196705,0.00003731354,0.00003412467,0.0000149284,0.001213323,0.0000294184,0.0005282617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09579737,"threshold_uncertainty_score":0.1904795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09464780890158499,"score_gpt":0.338414870930037,"score_spread":0.243767062028452,"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."}}