{"id":"W4223551742","doi":"10.1139/as-2021-0044","title":"Mapping tundra ecosystem plant functional type cover, height and aboveground biomass in Alaska and northwest Canada using unmanned aerial vehicles","year":2022,"lang":"en","type":"article","venue":"Arctic Science","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Bureau of Land Management; National Institute of Food and Agriculture; Nuclear Safety and Security Commission; Gwich'in Renewable Resources Board; U.S. Department of Agriculture; National Aeronautics and Space Administration; Parks Canada; National Science Foundation","keywords":"Environmental science; Tundra; Vegetation (pathology); Biomass (ecology); Forb; Deciduous; Graminoid; Evergreen; Remote sensing; Shrub; Satellite imagery; Plant functional type; Physical geography; Arctic; Ecosystem; Ecology; Grassland; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"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":[0.0001947028,0.0003239858,0.0001232816,0.0009589845,0.00074318,0.0005669173,0.0002598359,0.0001629173,0.000570363],"category_scores_gemma":[0.0003894668,0.0001339476,0.0002206068,0.000971403,0.00020229,0.0002784745,0.0002749691,0.0001303225,0.00008228362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002724071,"about_ca_system_score_gemma":0.002678146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9377856,"about_ca_topic_score_gemma":0.9705868,"domain_scores_codex":[0.9999032,0.000007328137,0.000005852561,0.00003128365,0.00003089289,0.00002145444],"domain_scores_gemma":[0.99978,0.00002996557,0.00002670684,0.0000101169,0.000116925,0.00003633003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001229065,0.00006973544,0.9188733,0.00005863058,0.00009820235,0.0001775321,0.0005159567,0.02758189,0.006977234,0.0002065161,0.000625028,0.04469314],"study_design_scores_gemma":[0.000009574712,0.00003112293,0.9316777,0.0000463223,0.00005664874,0.00005573114,0.001951766,0.06238937,0.001926968,0.0001177257,0.001707564,0.00002953987],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971212,0.0002192182,0.0006262645,0.00002064669,0.000003239128,0.000008399311,0.0008815104,0.00004023323,0.001079287],"genre_scores_gemma":[0.9960185,0.0002104035,0.002064402,0.000009870366,0.000001359723,0.000007735393,0.0009557832,0.000005573045,0.0007265728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06221437,"threshold_uncertainty_score":0.1251615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03704201906915106,"score_gpt":0.2081510944893506,"score_spread":0.1711090754201996,"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."}}