{"id":"W3006394683","doi":"10.5194/tc-14-549-2020","title":"Surface melt and the importance of water flow – an analysis based on high-resolution unmanned aerial vehicle (UAV) data for an Arctic glacier","year":2020,"lang":"en","type":"article","venue":"The cryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Arctic Institute of North America","keywords":"Glacier mass balance; Glacier; Albedo (alchemy); Geology; Arctic; Digital elevation model; Remote sensing; Environmental science; Climatology; Meteorology; 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":[0.0005941403,0.0004062296,0.0002870541,0.001021671,0.0003513204,0.0005738472,0.0002551129,0.0003426289,0.000298487],"category_scores_gemma":[0.001035633,0.000159156,0.0008155144,0.0006753957,0.0002976845,0.0004637672,0.0002559942,0.000344666,0.00009314754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009283296,"about_ca_system_score_gemma":0.0004362414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07090712,"about_ca_topic_score_gemma":0.06141014,"domain_scores_codex":[0.9998193,0.00002980589,0.00001399871,0.00005277477,0.00005317616,0.00003103202],"domain_scores_gemma":[0.9993958,0.0002084318,0.0001011049,0.000075018,0.0001649505,0.00005451194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000697618,0.0003542712,0.5350893,0.00009502531,0.0004247439,0.0004423437,0.0003124794,0.4199367,0.01786243,0.0003086049,0.0009499782,0.02352659],"study_design_scores_gemma":[0.00002694416,0.0001090698,0.3807514,0.00001753704,0.00006229393,0.00006920931,0.0001959406,0.6133998,0.004542607,0.0001117378,0.0006837292,0.00002971688],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988769,0.0000532034,0.0004143031,0.0000208957,0.000005129138,0.000004882798,0.000379769,0.00004345691,0.0002015173],"genre_scores_gemma":[0.9982634,0.00002812797,0.0007321435,0.00000500735,0.000004474191,0.000003843261,0.0009032608,0.00000785645,0.00005179317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07090712,"threshold_uncertainty_score":0.1409888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03564810663027443,"score_gpt":0.2368978906810554,"score_spread":0.2012497840507809,"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."}}