{"id":"W4321490648","doi":"10.1175/jhm-d-22-0067.1","title":"Investigating the Role of Shrub Height and Topography in Snow Accumulation on Low-Arctic Tundra using UAV-Borne Lidar","year":2023,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Center for Northern Studies","funders":"Fondation BNP Paribas; Natural Sciences and Engineering Research Council of Canada; Institut Polaire Français Paul Emile Victor; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Snow; Vegetation (pathology); Snow field; Tundra; Permafrost; Shrub; Physical geography; Arctic; Snow line; Lidar; Environmental science; Geology; Atmospheric sciences; Remote sensing; Geomorphology; Geography; Ecology; Snow cover; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001965543,0.0002565711,0.0001916609,0.0005038204,0.0003896531,0.0004621899,0.0002676573,0.0001936484,0.0007153988],"category_scores_gemma":[0.0003593296,0.0001305627,0.0001616685,0.0006045763,0.0001312158,0.000229347,0.0001437586,0.0001447461,0.0001656131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009490842,"about_ca_system_score_gemma":0.000782451,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5192686,"about_ca_topic_score_gemma":0.6900814,"domain_scores_codex":[0.9999179,0.00001437436,0.000002316457,0.00001962238,0.0000227763,0.00002312545],"domain_scores_gemma":[0.9997389,0.00004812589,0.0000268062,0.00001038384,0.0001413054,0.00003440419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002022253,0.00009352404,0.9218112,0.00006368304,0.00008002236,0.0002566074,0.0003891328,0.00860173,0.04660546,0.00006711679,0.0003737346,0.02145561],"study_design_scores_gemma":[0.000006359962,0.00003800524,0.9586801,0.00001138735,0.00002242061,0.00004095609,0.0004551554,0.0382578,0.002208158,0.00001636652,0.0002539313,0.000009259269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987797,0.00003663556,0.0004032624,0.00001273155,0.000001804991,0.000006433945,0.0002337635,0.00002007258,0.0005056353],"genre_scores_gemma":[0.9989206,0.00002566698,0.0006503717,0.000007601896,9.988642e-7,0.000003568742,0.0001744164,0.000002649981,0.0002141953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5192686,"threshold_uncertainty_score":0.967125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04971675322183312,"score_gpt":0.2806852807986905,"score_spread":0.2309685275768574,"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."}}