{"id":"W3084171198","doi":"10.1017/jog.2020.57","title":"Evaluating the transferability of empirical models of debris-covered glacier melt","year":2020,"lang":"en","type":"article","venue":"Journal of Glaciology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Indian Institute of Science; Division of Mathematical Sciences; National Aeronautics and Space Administration","keywords":"Glacier; Debris; Glacier mass balance; Geology; Climatology; Longwave; Forcing (mathematics); Shortwave; Rock glacier; Environmental science; Atmospheric sciences; Geomorphology; Radiative transfer","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007304155,0.0000692356,0.0003497553,0.00001152194,0.00006364015,0.000003529533,0.0002133886,0.00005121398,0.0004824116],"category_scores_gemma":[0.0004212494,0.00003919012,0.0001559221,0.0001709547,0.0001804376,0.00008877842,0.000009854954,0.0001752078,0.000001826402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003189064,"about_ca_system_score_gemma":0.0001039907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000123956,"about_ca_topic_score_gemma":0.00008787465,"domain_scores_codex":[0.9987748,0.0002102257,0.0005873637,0.00008713965,0.0002178472,0.0001226307],"domain_scores_gemma":[0.998705,0.0006633763,0.0002794103,0.0000894763,0.0002064176,0.00005631848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007474403,0.0000458279,0.87915,0.00004689129,0.0001779018,0.000003498591,0.006826982,0.09332141,0.001245565,0.0001455553,0.0006221019,0.01766685],"study_design_scores_gemma":[0.000616189,0.001923864,0.8962187,0.00001024198,0.00008475807,0.00001927484,0.001375195,0.09457959,0.000187618,0.004205536,0.0007111841,0.00006788433],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913174,0.001131506,0.002478759,0.004628069,0.000144016,0.00006924021,0.00002126044,0.000002075291,0.0002076637],"genre_scores_gemma":[0.9975727,0.0001287318,0.001553026,0.0006352949,0.0001027516,1.70856e-7,0.000001822359,0.000001369219,0.000004186553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01759896,"threshold_uncertainty_score":0.5282069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2008806097975954,"score_gpt":0.3576448800554314,"score_spread":0.156764270257836,"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."}}