{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001689145,0.0001121164,0.0001319735,0.00003800384,0.0009955229,0.0007963922,0.001090832,0.00002921717,0.0008356018],"category_scores_gemma":[0.000179953,0.00006988881,0.00001155966,0.0005182585,0.000493659,0.0008149069,0.0002788963,0.000101691,0.0003564627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000211546,"about_ca_system_score_gemma":0.0001720185,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002702565,"about_ca_topic_score_gemma":0.2376341,"domain_scores_codex":[0.9982238,0.00008675138,0.0001992042,0.0005692502,0.0004876279,0.000433356],"domain_scores_gemma":[0.997978,0.0002582198,0.00006659494,0.001422526,0.00006401293,0.0002106601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002352817,0.00001328159,0.9215294,0.0001794709,0.00001675865,0.0002422478,0.00042224,0.0000118762,0.0003284639,0.0002609426,0.05148223,0.02548955],"study_design_scores_gemma":[0.0001602328,0.00002541031,0.5721593,0.00006407056,0.00001374029,0.0004126465,0.001764632,0.01019202,0.00004901339,0.00001559392,0.4149838,0.0001595414],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3506198,0.008243023,0.00003824138,0.004406302,0.003240496,0.0005784367,0.6212839,0.000114728,0.01147503],"genre_scores_gemma":[0.8985668,0.0005522015,0.00009726716,0.0002809297,0.0002404498,9.022392e-7,0.1001196,0.000002972238,0.0001388428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5479471,"threshold_uncertainty_score":0.9149254,"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."}}