{"id":"W4392758296","doi":"10.5194/egusphere-egu24-13030","title":"Towards a Deep Learning-based Spatio-temporal Fusion Approach for Accurately Improving Snow Cover Mapping: A Case Study in the Moroccan Atlas Mountains with Performance Evaluation","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Atlas (anatomy); Cover (algebra); Snow cover; Cartography; Snow; Remote sensing; Computer science; Artificial intelligence; Geography; Geology; Meteorology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00108123,0.0008484376,0.0004528823,0.0006044072,0.0003981436,0.0006327233,0.0006363913,0.0006222225,0.0005075294],"category_scores_gemma":[0.001108041,0.0001112161,0.0003587164,0.0004906169,0.0002926465,0.0005053947,0.0005646565,0.0004044362,0.0001186509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048262,"about_ca_system_score_gemma":0.0006752805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03231386,"about_ca_topic_score_gemma":0.03359859,"domain_scores_codex":[0.9997396,0.0000651755,0.00001592973,0.00005554812,0.00005503474,0.00006863243],"domain_scores_gemma":[0.9996371,0.0001203153,0.00003091302,0.00003382736,0.000143163,0.00003475962],"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":[0.0007214113,0.0005179552,0.04037834,0.0002806357,0.0002516339,0.001899638,0.0003058271,0.6680761,0.02184804,0.001899933,0.004827562,0.2589929],"study_design_scores_gemma":[0.00001217345,0.00009743839,0.007013039,0.000008900642,0.00003332377,0.00005874407,0.00008968684,0.9877351,0.003863931,0.0004636611,0.0006157101,0.000008244711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381272,0.001327176,0.05590801,0.0007107515,0.00007714997,0.00007342,0.0003911145,0.0007111189,0.002674058],"genre_scores_gemma":[0.9850566,0.0001156552,0.01391426,0.00004651125,0.00001582381,0.00001367928,0.0002190376,0.00001244014,0.0006060905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03231386,"threshold_uncertainty_score":0.06425154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08140225540542557,"score_gpt":0.2902533132522506,"score_spread":0.208851057846825,"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."}}