{"id":"W7105765376","doi":"10.14288/1.0450706","title":"Mapping vegetation structure and carbon dynamics across the Canadian forest-tundra ecotone using multi-scale remote sensing","year":2025,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tundra; Ecotone; Vegetation (pathology); Climate change; Taiga; Boreal; Precipitation; Satellite imagery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0002962024,0.0003684036,0.0001892773,0.001588251,0.001171201,0.0009673219,0.0005991163,0.0002468026,0.000568054],"category_scores_gemma":[0.000710448,0.0001938535,0.0004362204,0.003000533,0.0002999136,0.0003301656,0.0003817007,0.000358964,0.000118196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009881414,"about_ca_system_score_gemma":0.00997745,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9912658,"about_ca_topic_score_gemma":0.9965318,"domain_scores_codex":[0.9997587,0.00001046982,0.000006618593,0.00006195104,0.00009278682,0.00006941225],"domain_scores_gemma":[0.9996058,0.00003987244,0.00005455616,0.00001946277,0.0002225118,0.00005774657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009436894,0.00009477408,0.910136,0.0001647616,0.0002095375,0.0001260503,0.001157875,0.01344526,0.007608848,0.0007548959,0.004078783,0.06212872],"study_design_scores_gemma":[0.000005583321,0.00001063608,0.9850141,0.00002430376,0.00002857918,0.00001872681,0.0007675793,0.01075537,0.0005125784,0.00006167517,0.002783088,0.00001776845],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989078,0.0004958012,0.0009923724,0.0001838959,0.000006931395,0.00003595962,0.00575504,0.00007852423,0.003373415],"genre_scores_gemma":[0.9900665,0.0004994713,0.004212351,0.00005584052,0.000003119441,0.00002291384,0.004030979,0.00001138455,0.001097359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009881414,"threshold_uncertainty_score":0.07169497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471038222898783,"score_gpt":0.1970975499947736,"score_spread":0.1823871677657858,"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."}}