{"id":"W4411003297","doi":"10.5194/tc-19-2017-2025","title":"Evaluation of the Snow Climate Change Initiative (Snow CCI) snow-covered area product within a mountain snow water equivalent reanalysis","year":2025,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Nuclear Safety and Security Commission; European Space Agency; National Aeronautics and Space Administration","keywords":"Snow; Water equivalent; Climate change; Environmental science; Snow field; Snow cover; Climatology; Physical geography; Meteorology; Geography; Geology","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":[0.006415111,0.0005818421,0.0005100089,0.001053644,0.0003199946,0.001274201,0.0006378317,0.0004282123,0.0005489708],"category_scores_gemma":[0.004830318,0.0002280907,0.0008066014,0.001539813,0.0002289134,0.001113592,0.0005993319,0.0004048771,0.0002656522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009457379,"about_ca_system_score_gemma":0.0009152478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04786923,"about_ca_topic_score_gemma":0.04475048,"domain_scores_codex":[0.9986032,0.0005166912,0.00009463586,0.0002676659,0.0004607402,0.00005717522],"domain_scores_gemma":[0.9974801,0.0005463188,0.0002911328,0.0002609362,0.001248404,0.0001731057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001754399,0.0008540401,0.5276572,0.000507258,0.002150225,0.0003117248,0.0004528356,0.2763833,0.01551826,0.00150468,0.01312836,0.1597778],"study_design_scores_gemma":[0.0002160383,0.0006185712,0.4569956,0.00006776238,0.000280633,0.00004828826,0.0002816433,0.5302231,0.005736441,0.000246681,0.005211285,0.00007400102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740881,0.0005037514,0.008346911,0.0002394206,0.00008618935,0.0002896224,0.01241226,0.0006908664,0.003342868],"genre_scores_gemma":[0.9534754,0.0001812684,0.0230917,0.00006512363,0.00003429137,0.0001709506,0.02236399,0.0001054715,0.0005116722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04786923,"threshold_uncertainty_score":0.09518123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06733577171220687,"score_gpt":0.2715404479622927,"score_spread":0.2042046762500858,"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."}}