{"id":"W2758275142","doi":"10.1002/hyp.11364","title":"Spatio‐temporal variability of Great Lakes basin snow cover ablation events","year":2017,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Naval Academy; Climate Program Office; U.S. Army Corps of Engineers; National Oceanic and Atmospheric Administration; Northwestern University","keywords":"Snowmelt; Structural basin; Snow; Drainage basin; Environmental science; Ablation zone; Bay; Ablation; Hydrology (agriculture); Annual cycle; Climatology; Geology; Physical geography; Oceanography; Geography; Geomorphology","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":[0.0001622217,0.00008110744,0.00008579538,0.0005713211,0.0002165649,0.0003141419,0.0001272333,0.00009633446,0.0005323373],"category_scores_gemma":[0.0004792337,0.00008049242,0.0001135399,0.0007781012,0.0001540405,0.0001741721,0.0002888418,0.0001055942,0.00009207735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004738934,"about_ca_system_score_gemma":0.0003234285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1195864,"about_ca_topic_score_gemma":0.2625011,"domain_scores_codex":[0.9999219,0.00001254711,0.000006135523,0.00002391575,0.0000204846,0.0000149961],"domain_scores_gemma":[0.9996725,0.00007268825,0.0001058931,0.00002445587,0.00008018938,0.00004415312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003220365,0.00001168538,0.9924003,0.00001363012,0.00006072052,0.00007118996,0.0003733859,0.0008409377,0.001246622,0.0000804789,0.001062397,0.003806454],"study_design_scores_gemma":[7.782497e-7,0.000002077687,0.9991384,0.000001847091,0.000002472442,0.000008720469,0.00006367538,0.0004542237,0.00004680812,0.000007115967,0.0002728328,9.585616e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981427,0.00006167843,0.00004807655,0.00003713215,0.000001841715,0.000002057584,0.001159211,0.000009831293,0.0005375291],"genre_scores_gemma":[0.9986242,0.00005013439,0.00005234929,0.000007488209,0.00000307997,0.000004530779,0.001101983,0.000001624423,0.0001545539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8804137,"threshold_uncertainty_score":0.2377806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03884592900063261,"score_gpt":0.2501734899390409,"score_spread":0.2113275609384083,"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."}}