{"id":"W4250513684","doi":"10.5194/tc-2020-207","title":"A low-cost method for monitoring snow characteristics at remote field sites","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University; ArcticNet; W. Garfield Weston Foundation; Parks Canada","keywords":"Snow; Tundra; Environmental science; Permafrost; Snow field; Subarctic climate; Physical geography; Remote sensing; Habitat; Vegetation (pathology); Arctic; Snowmelt; Climatology; Ecology; Geography; Geology; Meteorology; Snow cover","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":[0.0002725997,0.0004518825,0.0003058005,0.001300237,0.0003242748,0.0003596077,0.0006331975,0.0003214571,0.002965282],"category_scores_gemma":[0.0004735856,0.0002056526,0.000240892,0.001097459,0.0001446443,0.0004783707,0.0003883829,0.0002829258,0.001128792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000237638,"about_ca_system_score_gemma":0.0003183205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003108336,"about_ca_topic_score_gemma":0.01415237,"domain_scores_codex":[0.9997014,0.00004144609,0.00001438471,0.00009993619,0.000122625,0.00002008074],"domain_scores_gemma":[0.9995254,0.00008608594,0.0001103786,0.00008539874,0.0001686487,0.00002413533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003169397,0.0002714285,0.1709495,0.000400979,0.0001020582,0.0001316655,0.0002468019,0.004428461,0.4702627,0.000282322,0.002165449,0.3504417],"study_design_scores_gemma":[0.000100584,0.0008145678,0.6932813,0.0000848066,0.0002069799,0.0008391052,0.0005388986,0.1025846,0.1897972,0.0005458095,0.01109058,0.0001156205],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6500639,0.000375118,0.3381971,0.00008447067,0.00008193858,0.0004240157,0.004595851,0.002132442,0.004045178],"genre_scores_gemma":[0.7276543,0.0001856612,0.2675918,0.00006539036,0.00003733108,0.0004564472,0.001803386,0.00007311203,0.002132631],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003108336,"threshold_uncertainty_score":0.009919822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07473862401729081,"score_gpt":0.3036228641285317,"score_spread":0.2288842401112409,"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."}}