{"id":"W4412954834","doi":"10.5194/tc-19-2797-2025","title":"A random-forest-derived 35-year snow phenology record reveals climate trends in the Yukon River Basin","year":2025,"lang":"en","type":"article","venue":"The cryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineer Research and Development Center; U.S. Army Corps of Engineers","keywords":"Snow; Phenology; Physical geography; Structural basin; Climate change; Drainage basin; Climatology; Hydrology (agriculture); Environmental science; Geology; Geography; Ecology; Meteorology; Oceanography; Geomorphology; Cartography","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":[0.0002098091,0.0002012116,0.0002050434,0.0005991711,0.0002697061,0.0003659216,0.0002571859,0.0002192375,0.0004588022],"category_scores_gemma":[0.0004584689,0.0001404453,0.0004173573,0.0007670189,0.0001289138,0.0003218401,0.0002207288,0.00009878438,0.0001307596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005831064,"about_ca_system_score_gemma":0.0007732788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1339044,"about_ca_topic_score_gemma":0.222293,"domain_scores_codex":[0.9999117,0.00001321976,0.000008018481,0.00003201321,0.00001264665,0.00002252397],"domain_scores_gemma":[0.9998305,0.00002443786,0.00002618474,0.00002351861,0.00007593407,0.00001939417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000144755,0.00005477026,0.8926743,0.0001638614,0.000265733,0.0002266283,0.000285044,0.0542093,0.01312,0.0003139279,0.00217859,0.03636314],"study_design_scores_gemma":[0.0000191259,0.00003102075,0.8793974,0.00002335434,0.00006984298,0.00008770671,0.0002039571,0.1167284,0.001113013,0.0001514064,0.002150905,0.00002377011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996089,0.000119614,0.00136935,0.00002859601,0.000003863014,0.000007083783,0.001977563,0.00009522065,0.0003096902],"genre_scores_gemma":[0.9966384,0.00003518659,0.001127602,0.000008095717,0.000001687015,0.000007654622,0.002078573,0.00001020453,0.00009258098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1339044,"threshold_uncertainty_score":0.2662501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679132401277358,"score_gpt":0.2338746973983001,"score_spread":0.2170833733855266,"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."}}