{"id":"W6910860707","doi":"10.5065/hsbv-b152","title":"Ensemble Historical Gridded Daily Temperature and Bias Adjusted Precipitation for Alaska and the Yukon","year":2020,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precipitation; Ensemble average; Interpolation (computer graphics); Range (aeronautics); Multivariate interpolation; Ensemble forecasting; Atmospheric temperature","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":[0.0004893836,0.0009866261,0.0006265052,0.001588722,0.0004827814,0.0009423825,0.001479617,0.0008658977,0.01106028],"category_scores_gemma":[0.001318751,0.0004447791,0.0006359312,0.004152364,0.0003043869,0.0009421307,0.0007743111,0.0008152304,0.01139595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290983,"about_ca_system_score_gemma":0.002390483,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1838538,"about_ca_topic_score_gemma":0.2529595,"domain_scores_codex":[0.9997206,0.00002683285,0.00003730947,0.00008705682,0.00007562381,0.00005243106],"domain_scores_gemma":[0.9992974,0.00006889546,0.00008088142,0.0001544094,0.0003297151,0.00006865509],"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":[0.0001544908,0.0000684444,0.01450048,0.0006514927,0.0001485028,0.0001255451,0.0001152499,0.004349021,0.0003874501,0.001354401,0.968197,0.009947971],"study_design_scores_gemma":[0.0002714497,0.00003618342,0.07391959,0.0003614565,0.00007845212,0.0001947814,0.0004928354,0.005775219,0.001167013,0.001968276,0.915634,0.0001007316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001868556,0.00004826342,0.0001116726,0.00003866538,0.00002112315,0.0000081224,0.9970427,0.0002061397,0.0006546383],"genre_scores_gemma":[0.00199796,0.00003096115,0.0002274269,0.000008618189,0.00000224665,0.00002552877,0.9972362,0.00002467993,0.0004464211],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8161462,"threshold_uncertainty_score":0.3655673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07239907893792594,"score_gpt":0.3031175664363913,"score_spread":0.2307184874984654,"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."}}