{"id":"W4390519502","doi":"10.5194/tc-18-17-2024","title":"Evaluation of reanalysis data and dynamical downscaling for surface energy balance modeling at mountain glaciers in western Canada","year":2024,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Downscaling; Weather Research and Forecasting Model; Glacier; Climatology; Environmental science; Energy balance; Forcing (mathematics); Wind speed; Meteorology; Climate model; Climate change; Geology; Precipitation; Geography","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":[0.0009026246,0.0007491958,0.0003871912,0.0005452922,0.0009382805,0.001007496,0.001276105,0.0004434594,0.0009688206],"category_scores_gemma":[0.002049987,0.0003747844,0.0006909095,0.0009121873,0.0004339764,0.0005217524,0.0003947321,0.0004987479,0.000134859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007336858,"about_ca_system_score_gemma":0.007566481,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9581428,"about_ca_topic_score_gemma":0.9487493,"domain_scores_codex":[0.9996824,0.00005675483,0.00001760011,0.00008807999,0.00009005514,0.00006497281],"domain_scores_gemma":[0.9990539,0.0001484293,0.00006042422,0.00007006158,0.0005642985,0.0001030095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005371628,0.0002579231,0.2775187,0.00007909623,0.0003791293,0.0001720325,0.0002640799,0.6879778,0.004620783,0.0005179726,0.001894898,0.02578053],"study_design_scores_gemma":[0.000163224,0.00006929196,0.1900689,0.00002007677,0.0000983048,0.00001472369,0.0002508331,0.8052788,0.002716691,0.0000936381,0.001174719,0.00005081659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970297,0.0000679309,0.0006182858,0.00007990967,0.00001209209,0.00002559368,0.001112608,0.0001677472,0.0008860794],"genre_scores_gemma":[0.9954235,0.00004554486,0.002148916,0.00001982777,0.000003754442,0.00001683199,0.001956174,0.00002866398,0.0003568263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04185724,"threshold_uncertainty_score":0.08420742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03873313478285102,"score_gpt":0.2600347361992688,"score_spread":0.2213016014164178,"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."}}