{"id":"W2789112328","doi":"10.5065/5bjc-w635","title":"Daily Gridded North American Snowfall","year":2017,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; National weather service; Environmental science; Interpolation (computer graphics); Climatology; Meteorology; Grid cell; Grid; Sampling (signal processing); Elevation (ballistics); Range (aeronautics); Geography; Geology; Mathematics; Computer science; Geodesy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000542551,0.0008724951,0.0006391531,0.001558586,0.0004354186,0.0008343041,0.001418893,0.000495336,0.01600773],"category_scores_gemma":[0.001402026,0.0003055569,0.0006006775,0.003110185,0.0002176066,0.0005881683,0.0007598248,0.0008816898,0.01497646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000879812,"about_ca_system_score_gemma":0.001968821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06795806,"about_ca_topic_score_gemma":0.09912764,"domain_scores_codex":[0.9996443,0.00005262954,0.0000289102,0.0001060412,0.0001200089,0.00004807532],"domain_scores_gemma":[0.9991781,0.00005601578,0.00006829754,0.0001237841,0.0005021449,0.00007167267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005121562,0.00003126476,0.003644154,0.0001333062,0.00004585771,0.00002136131,0.00002620952,0.001143337,0.00008705834,0.0005554716,0.9906798,0.003580922],"study_design_scores_gemma":[0.00016413,0.00001206544,0.02661918,0.0001381394,0.00002949652,0.00004942347,0.0002022985,0.003945738,0.000536452,0.001019536,0.9672515,0.00003198988],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00205921,0.00004756125,0.0001571715,0.00007211279,0.00004876418,0.00001448536,0.9961718,0.0002620621,0.001166714],"genre_scores_gemma":[0.00263815,0.000041829,0.000471383,0.00002362354,0.00001052126,0.00008560257,0.9954575,0.00006173195,0.001209711],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06795806,"threshold_uncertainty_score":0.135125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0673517627599012,"score_gpt":0.3095880087994462,"score_spread":0.242236246039545,"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."}}