{"id":"W4235542690","doi":"10.5194/hessd-6-3687-2009","title":"Interrelationships between MODIS/Terra remotely sensed snow cover and the hydrometeorology of the Quesnel River Basin, British Columbia, Canada","year":2009,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"Goddard Space Flight Center; Natural Sciences and Engineering Research Council of Canada; Government of Canada; University of Northern British Columbia; National Aeronautics and Space Administration","keywords":"Snow; Environmental science; Hydrometeorology; Moderate-resolution imaging spectroradiometer; Streamflow; Snowmelt; Snow cover; Climatology; Spectroradiometer; Cloud cover; Atmospheric sciences; Drainage basin; Physical geography; Hydrology (agriculture); Precipitation; Meteorology; Satellite; Geography; Reflectivity; Geology; Cartography; Cloud computing","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":[0.0004013165,0.0002472836,0.0002562179,0.001226263,0.00171687,0.001451611,0.000759921,0.0002636558,0.003507648],"category_scores_gemma":[0.001518084,0.0002193751,0.0002281566,0.002323868,0.0006259734,0.0002774378,0.00048274,0.0003942476,0.0003091393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01514409,"about_ca_system_score_gemma":0.01449322,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958431,"about_ca_topic_score_gemma":0.9985109,"domain_scores_codex":[0.9996025,0.00004507645,0.0000244131,0.00009972903,0.000125675,0.0001025738],"domain_scores_gemma":[0.9973483,0.0002262647,0.0002220063,0.00007414108,0.00167514,0.0004542198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007084566,0.00002337274,0.9842094,0.00005002778,0.0001062203,0.0001589966,0.0005226301,0.0007344147,0.000823136,0.0002201177,0.003935137,0.009145724],"study_design_scores_gemma":[0.000002937341,0.000002361293,0.9971733,0.00002578684,0.00001372613,0.00001772601,0.0007271362,0.0005473239,0.00005794733,0.00002131196,0.001402443,0.000007880029],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873432,0.001034262,0.0001733309,0.0005517939,0.00001986991,0.00002221989,0.004063473,0.00003608367,0.006755822],"genre_scores_gemma":[0.9952865,0.0003048165,0.0002238781,0.00007484018,0.000003881119,0.00001290856,0.00128763,0.00001076713,0.002794803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01514409,"threshold_uncertainty_score":0.1098785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952539842219642,"score_gpt":0.1912472031002137,"score_spread":0.1717218046780173,"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."}}