{"id":"W2965445377","doi":"10.3389/feart.2019.00182","title":"Sub-kilometer Precipitation Datasets for Snowpack and Glacier Modeling in Alpine Terrain","year":2019,"lang":"en","type":"article","venue":"Frontiers in Earth Science","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Center for Neuroscience and Regenerative Medicine; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Snowpack; Snow; Precipitation; Environmental science; Glacier mass balance; Glacier; Climatology; Terrain; Meteorology; Geology; Geography; Geomorphology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006553387,0.00008488211,0.000136849,0.0001296099,0.0001152449,0.00006424962,0.0001773151,0.00002765351,0.00005352588],"category_scores_gemma":[0.00009750827,0.00007413852,0.00001579561,0.0006626237,0.0001373401,0.0006034584,0.00002223046,0.00006744289,0.00001169096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007164157,"about_ca_system_score_gemma":0.00004763195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003797647,"about_ca_topic_score_gemma":0.002314341,"domain_scores_codex":[0.9989437,0.00001309665,0.0001828314,0.0003453148,0.0001958607,0.0003192254],"domain_scores_gemma":[0.9996813,0.0000468616,0.00003696862,0.000148569,0.00002768711,0.00005864754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002441008,0.000007771464,0.9490853,0.00001294083,0.000001880481,5.620452e-7,0.0006211959,0.02427772,0.00009069025,0.00001243579,0.0004021903,0.0254629],"study_design_scores_gemma":[0.0002519601,0.00004230244,0.4878871,0.00001275589,0.000001254476,4.387992e-7,0.0004384711,0.5095483,0.00001481124,0.0003644127,0.001364479,0.00007368659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898448,0.0004992966,0.008094214,0.000173398,0.0007157278,0.0003986749,0.0001256855,0.000008124854,0.0001400913],"genre_scores_gemma":[0.9581671,0.0001064652,0.04132517,0.0001808567,0.00002454027,0.000004573816,0.00009859446,0.000002081231,0.00009062917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4852706,"threshold_uncertainty_score":0.3023281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01915739491515992,"score_gpt":0.2291581139312882,"score_spread":0.2100007190161282,"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."}}