{"id":"W1849658156","doi":"10.5194/tc-10-623-2016","title":"Microwave snow emission modeling uncertainties in boreal and subarctic environments","year":2016,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Northern Studies; Université de Sherbrooke","funders":"Center for Neuroscience and Regenerative Medicine; Institut Polaire Français Paul Emile Victor; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Centre National de la Recherche Scientifique; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Snow; Environmental science; Spatial variability; Firn; Atmospheric sciences; Brightness temperature; Brightness; Geology; Geomorphology; Physics","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":[0.001278104,0.0006977351,0.0003215202,0.0003192973,0.0002556513,0.0007600699,0.0006493052,0.0003934096,0.0003216389],"category_scores_gemma":[0.002074,0.00026435,0.0005448078,0.0003612324,0.0002912606,0.0006591794,0.0004147251,0.0002625535,0.000075011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008571649,"about_ca_system_score_gemma":0.0005384573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06628736,"about_ca_topic_score_gemma":0.05226563,"domain_scores_codex":[0.999691,0.0001037533,0.00001914598,0.00008888958,0.00005031097,0.00004693542],"domain_scores_gemma":[0.9990106,0.0005071335,0.0001914225,0.0001020917,0.0001454576,0.00004338268],"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":[0.0000874124,0.00003539235,0.07609485,0.00002477894,0.0001103152,0.00008856788,0.00005517675,0.9159144,0.002138524,0.0003992652,0.0001462707,0.004905045],"study_design_scores_gemma":[0.00002542692,0.00003220302,0.05460738,0.00001198526,0.00003822038,0.00003894504,0.00008678008,0.9430434,0.0009313239,0.0004989816,0.0006667948,0.00001866308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852219,0.0003057702,0.01231423,0.00009878438,0.00001614605,0.00001265488,0.000607287,0.0001950573,0.001228306],"genre_scores_gemma":[0.9976683,0.00006117427,0.001841441,0.00001118883,0.000007496239,0.000004987308,0.0003153542,0.00001520964,0.00007481252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06628736,"threshold_uncertainty_score":0.1318031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719023791633463,"score_gpt":0.2023874466822246,"score_spread":0.1851972087658899,"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."}}