{"id":"W4400085216","doi":"10.5194/hess-28-2745-2024","title":"How does a warm and low-snow winter impact the snow cover dynamics in a humid and discontinuous boreal forest? Insights from observations and modeling in eastern Canada","year":2024,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bio-K+ International (Canada); Université Laval; CentrEau - Quebec Water Management Research Centre; Center for Northern Studies","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Snow; Snow cover; Taiga; Boreal; Environmental science; Climatology; Physical geography; Forest cover; Atmospheric sciences; Meteorology; Geography; Geology; Ecology; Forestry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002655532,0.0003818857,0.0003548551,0.000481937,0.001370496,0.001108916,0.001028117,0.0004359245,0.0007687441],"category_scores_gemma":[0.0006415683,0.0002633656,0.0005269912,0.001003019,0.0006667172,0.0004158734,0.0003588013,0.0004006057,0.00007784682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01203088,"about_ca_system_score_gemma":0.009328538,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9883131,"about_ca_topic_score_gemma":0.9899373,"domain_scores_codex":[0.9998451,0.00001198137,0.00000679477,0.00003992762,0.00002634415,0.00006978392],"domain_scores_gemma":[0.9996982,0.00006199717,0.0000338525,0.00001587924,0.0001042363,0.00008581652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002020452,0.0001979835,0.8833928,0.00008479671,0.000169093,0.0002964019,0.0008429452,0.1000524,0.004076674,0.0005719651,0.001379958,0.008732848],"study_design_scores_gemma":[0.00005532052,0.00003358685,0.7568728,0.00002860446,0.00007815294,0.00004376076,0.001353728,0.2394047,0.0005606239,0.0001776722,0.001348395,0.00004242328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987296,0.00008897984,0.0001382131,0.000046222,0.000001840337,0.000005726571,0.0004415677,0.00001844879,0.0005293431],"genre_scores_gemma":[0.9991667,0.00007383224,0.0002129391,0.00001155941,0.000001162006,0.000003021022,0.0003648851,0.000005114641,0.000160837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01203088,"threshold_uncertainty_score":0.08729059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01959003021091003,"score_gpt":0.2083265748181147,"score_spread":0.1887365446072047,"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."}}