{"id":"W2052300641","doi":"10.1029/2012eo310011","title":"Hemispheric snow water equivalent: The need for a synergistic approach","year":2012,"lang":"en","type":"article","venue":"Eos","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Snow; Snowpack; Environmental science; Water equivalent; Snowmelt; Hydropower; Atmospheric sciences; Forage; Water resources; Hydrology (agriculture); Physical geography; Meteorology; Geology; Ecology; Geography; Geotechnical engineering","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":[0.006814715,0.001006758,0.001646987,0.002507771,0.000820272,0.003080305,0.001714825,0.001104937,0.005756493],"category_scores_gemma":[0.01011325,0.0004658698,0.0008364692,0.003448874,0.0007974553,0.006928854,0.004427802,0.002157557,0.0009066646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234514,"about_ca_system_score_gemma":0.001965971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01677761,"about_ca_topic_score_gemma":0.02692118,"domain_scores_codex":[0.9987458,0.0006376285,0.00006810334,0.0002005595,0.0002719998,0.00007586934],"domain_scores_gemma":[0.995795,0.001298828,0.0002733198,0.0006010456,0.001563302,0.0004686028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004508883,0.0001528502,0.07942625,0.001275314,0.001355178,0.0004274873,0.0008249366,0.01757545,0.003402409,0.08094743,0.07188582,0.742276],"study_design_scores_gemma":[0.0001707506,0.0002970257,0.1637801,0.002281852,0.001308018,0.0006844637,0.005934429,0.07068217,0.002647816,0.3596895,0.392177,0.0003468468],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1423848,0.1880128,0.3526956,0.1353683,0.009214601,0.0007660947,0.01093364,0.002071129,0.1585531],"genre_scores_gemma":[0.6351895,0.05846559,0.2767574,0.009837973,0.007159729,0.0005200227,0.003731902,0.0008398388,0.007498002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01677761,"threshold_uncertainty_score":0.03604013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03805300326719202,"score_gpt":0.2250277567589383,"score_spread":0.1869747534917463,"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."}}