{"id":"W2061786841","doi":"10.5194/hessd-12-4157-2015","title":"Uncertainty analysis for evaluating the accuracy of snow depth measurements","year":2015,"lang":"en","type":"article","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Snow; Environmental science; Observational error; Mean squared error; Outlier; Range (aeronautics); Measured depth; Classification of discontinuities; Meteorology; Remote sensing; Geology; Statistics; Mathematics; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01947379,0.001139654,0.0009785122,0.007273396,0.0008004294,0.001750481,0.001694287,0.0009920307,0.0008433557],"category_scores_gemma":[0.05465022,0.0004232779,0.001793809,0.003434404,0.0009735674,0.001783911,0.001802376,0.0008327251,0.0001682021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001558709,"about_ca_system_score_gemma":0.001396529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006936391,"about_ca_topic_score_gemma":0.004869605,"domain_scores_codex":[0.9830877,0.0044461,0.001463807,0.001539384,0.009036059,0.0004268925],"domain_scores_gemma":[0.9364622,0.04498199,0.005460251,0.00394464,0.008820912,0.0003300048],"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":[0.0008178839,0.0002169159,0.1476196,0.00147993,0.001973,0.000615406,0.0009727554,0.5841701,0.02872547,0.02243283,0.001923418,0.2090526],"study_design_scores_gemma":[0.00004952463,0.0005844581,0.07106723,0.0003866023,0.0003816945,0.0006793165,0.0006524807,0.8620512,0.03859232,0.01785179,0.007385506,0.0003178364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2093417,0.002652428,0.7794917,0.0001713266,0.0001084285,0.0002891777,0.001819007,0.0008846433,0.005241685],"genre_scores_gemma":[0.8598939,0.0004215389,0.1372555,0.00005170649,0.00006471929,0.0003065328,0.001496137,0.0001334673,0.000376599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01947379,"threshold_uncertainty_score":0.1029885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3077696288957412,"score_gpt":0.3618494478771749,"score_spread":0.05407981898143377,"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."}}