{"id":"W4404112088","doi":"10.2139/ssrn.5011706","title":"Next Generation Arctic Vegetation Maps: Aboveground Plant Biomass and Woody Dominance Mapped at 30 M Resolution Across the Tundra Biome","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Tundra; Biome; Dominance (genetics); Vegetation (pathology); Biomass (ecology); Arctic; Environmental science; Forestry; Geography; Arctic vegetation; Ecology; Physical geography; Biology; Ecosystem","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":[0.0007700536,0.0004969093,0.0003509767,0.001920798,0.0004240046,0.0008774043,0.0003411381,0.0004915161,0.006090076],"category_scores_gemma":[0.001082097,0.0003696469,0.0005144655,0.00256196,0.0001047681,0.0004826061,0.0006991899,0.0003650794,0.002376948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004485963,"about_ca_system_score_gemma":0.001012887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0943949,"about_ca_topic_score_gemma":0.162016,"domain_scores_codex":[0.9998237,0.00003125391,0.00000526496,0.00005081871,0.00004352267,0.0000454716],"domain_scores_gemma":[0.9994802,0.0000675832,0.00004697151,0.00007360685,0.0002382979,0.0000933936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001524045,0.0004115776,0.2980972,0.0006999412,0.001080508,0.0008699805,0.00187195,0.07659803,0.03025885,0.00658837,0.264076,0.3179236],"study_design_scores_gemma":[0.0001426211,0.00006281906,0.7172809,0.0002277184,0.0002424591,0.0003480391,0.0008715818,0.06537338,0.00511477,0.006026048,0.2042031,0.0001065296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3203449,0.001468522,0.02974109,0.000827406,0.0003005101,0.00007661714,0.6257331,0.003883505,0.01762431],"genre_scores_gemma":[0.4713627,0.001030113,0.07638051,0.0001979281,0.0001438141,0.0001663456,0.4412402,0.0006736057,0.008804766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0943949,"threshold_uncertainty_score":0.1876909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04174819167517947,"score_gpt":0.2628416446361639,"score_spread":0.2210934529609844,"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."}}