{"id":"W3158747095","doi":"10.5194/essd-13-5127-2021","title":"The Boreal–Arctic Wetland and Lake Dataset (BAWLD)","year":2021,"lang":"en","type":"article","venue":"Earth system science data","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ducks Unlimited Canada; University of Toronto; Dalhousie University; University of Waterloo; Université de Montréal; University of Alberta","funders":"Norges Forskningsråd; Vetenskapsrådet; Bundesministerium für Bildung und Forschung; National Aeronautics and Space Administration; National Science Foundation","keywords":"Permafrost; Wetland; Tundra; Environmental science; Peat; Boreal; Taiga; Thermokarst; Hydrology (agriculture); Arctic; Biome; Bog; Land cover; Physical geography; Ecosystem; Ecology; Geology; Land use; Oceanography; Geography","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":[0.000608518,0.0009993855,0.0007493993,0.00156573,0.0004764941,0.0008369201,0.001186511,0.0006999656,0.004629786],"category_scores_gemma":[0.001219639,0.0002904274,0.001010935,0.002131471,0.0002337486,0.0004722697,0.0009279979,0.0007414087,0.004764328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006300783,"about_ca_system_score_gemma":0.001079292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05483278,"about_ca_topic_score_gemma":0.09102612,"domain_scores_codex":[0.9995682,0.00007134255,0.00004836306,0.0001384854,0.000107292,0.00006641334],"domain_scores_gemma":[0.9993445,0.00008095623,0.0001152399,0.0001140994,0.0002477362,0.00009739349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004805407,0.0002150686,0.09038071,0.00156062,0.0008078369,0.0003091189,0.0002560736,0.00588498,0.003395468,0.001263589,0.8777301,0.01771594],"study_design_scores_gemma":[0.0007654487,0.0001259282,0.2692036,0.000423867,0.0002543989,0.0002894691,0.000595079,0.01900473,0.002690632,0.001020123,0.7055147,0.0001119577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01021866,0.0001540471,0.0003579255,0.0000623454,0.00003339528,0.00003185856,0.9878876,0.0004776132,0.0007765495],"genre_scores_gemma":[0.007134156,0.00003516173,0.0007794751,0.00002145932,0.000006958542,0.00005929128,0.9917007,0.00002593064,0.000236932],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05483278,"threshold_uncertainty_score":0.1090273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06211837631924387,"score_gpt":0.2699736976716027,"score_spread":0.2078553213523588,"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."}}