{"id":"W4252789801","doi":"10.5194/tc-2017-80","title":"Evaluation of different methods to model near-surface turbulent fluxes for an alpine glacier in the Cariboo Mountains, BC, Canada","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Northern British Columbia; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Eddy covariance; Sensible heat; Katabatic wind; Glacier; Turbulence; Latent heat; Environmental science; Atmospheric sciences; Atmospheric instability; Climatology; Wind speed; Meteorology; Geology; Physics; 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":[0.0006544589,0.001257554,0.0004104358,0.0005391494,0.0006939496,0.0007551166,0.0006725896,0.0004497517,0.000524219],"category_scores_gemma":[0.0009991813,0.0002291549,0.000518662,0.0003662165,0.0002462234,0.0003580333,0.0003416137,0.0005195071,0.0001132701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002031217,"about_ca_system_score_gemma":0.002370913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5605512,"about_ca_topic_score_gemma":0.4496545,"domain_scores_codex":[0.9998401,0.00002651982,0.00000998594,0.00004318839,0.00004597297,0.00003416232],"domain_scores_gemma":[0.999568,0.000132374,0.00002749281,0.00003010842,0.0002055129,0.00003643665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002244765,0.0002535737,0.05588431,0.00009153384,0.0001609607,0.0000758772,0.0001702241,0.8993275,0.006716948,0.0003541359,0.0004374063,0.03630309],"study_design_scores_gemma":[0.00002279325,0.00004041077,0.01073684,0.000005450337,0.0000111952,0.000005752659,0.00003959414,0.9875479,0.001399258,0.00003888005,0.0001432719,0.000008641646],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843416,0.0001723669,0.01308137,0.00004143337,0.0000191887,0.00005922848,0.0003888322,0.0004972514,0.00139868],"genre_scores_gemma":[0.9894617,0.00006104675,0.009295946,0.00001311561,0.000005211557,0.00003885029,0.0006581389,0.0000412209,0.0004247368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4394488,"threshold_uncertainty_score":0.8840736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1248689564800285,"score_gpt":0.36268368241854,"score_spread":0.2378147259385116,"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."}}