{"id":"W2591713612","doi":"10.3390/rs9030256","title":"Estimating Snow Mass and Peak River Flows for the Mackenzie River Basin Using GRACE Satellite Observations","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"Goddard Space Flight Center; Natural Resources Canada; National Aeronautics and Space Administration","keywords":"Snowmelt; Snow; Environmental science; Drainage basin; Climatology; Structural basin; Flood myth; Climate change; Hydrology (agriculture); Geology; Meteorology; Geography; Geomorphology","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":[0.0003112452,0.0004594526,0.000232145,0.001186947,0.0005405731,0.0005188959,0.0004679882,0.0002471204,0.0003994232],"category_scores_gemma":[0.0006572611,0.0002369615,0.0006838242,0.0009299253,0.0001752578,0.0005574384,0.0004785292,0.0002395448,0.000117263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002274181,"about_ca_system_score_gemma":0.002425041,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5716515,"about_ca_topic_score_gemma":0.6888155,"domain_scores_codex":[0.9998816,0.00001345044,0.000008911106,0.00004169533,0.00002529362,0.00002906016],"domain_scores_gemma":[0.9998571,0.00001930264,0.00003407627,0.0000179858,0.00004874363,0.00002278971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001417201,0.0001006778,0.8994614,0.00004477345,0.0003022719,0.0003089123,0.0003725153,0.06069512,0.004686039,0.0004552439,0.001576556,0.03185474],"study_design_scores_gemma":[0.00002819497,0.00002770464,0.7704656,0.00001683981,0.00008768566,0.00003980681,0.0004773288,0.2256204,0.001277845,0.0002124651,0.001705847,0.00004022798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968861,0.00005800317,0.0009829748,0.00003769917,0.000002239187,0.00001823957,0.001307936,0.00007227263,0.0006344729],"genre_scores_gemma":[0.9944015,0.00006960097,0.003023287,0.000009255965,0.000003057333,0.00002394415,0.002200145,0.00001364173,0.0002555811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4283485,"threshold_uncertainty_score":0.8617422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07893332339860512,"score_gpt":0.2669970896656179,"score_spread":0.1880637662670127,"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."}}