{"id":"W2899339736","doi":"10.3390/rs10111703","title":"Snow-Covered Soil Temperature Retrieval in Canadian Arctic Permafrost Areas, Using a Land Surface Scheme Informed with Satellite Remote Sensing Data","year":2018,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Northern Studies; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; Environment and Climate Change Canada; National Aeronautics and Space Administration","keywords":"Permafrost; Environmental science; Snow; Brightness temperature; Tundra; Snowpack; Remote sensing; Data assimilation; Satellite; Atmospheric sciences; Climatology; Arctic; Meteorology; Brightness; Geology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006364488,0.0003937104,0.0004308053,0.0002606039,0.000510328,0.0003984107,0.000277052,0.0002682028,0.0002072057],"category_scores_gemma":[0.0003186966,0.0003446537,0.00004573766,0.0009492144,0.0002330754,0.0006042143,0.00005819401,0.0005115733,0.0001078339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001582132,"about_ca_system_score_gemma":0.001007714,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7555224,"about_ca_topic_score_gemma":0.9844811,"domain_scores_codex":[0.9971416,0.0001314843,0.0004103078,0.0006946301,0.0004383244,0.001183676],"domain_scores_gemma":[0.9980105,0.0002156522,0.000156824,0.000885565,0.0002100273,0.0005214476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00284579,0.0000197948,0.7313778,0.0007482415,0.0002751229,0.004658913,0.01414379,0.004717772,0.07084666,0.000001562197,0.0005537792,0.1698107],"study_design_scores_gemma":[0.0008247326,0.00008538381,0.03952087,0.001401621,0.0000447457,0.001249702,0.0006922614,0.9498826,0.0008077759,0.00003096206,0.004774202,0.0006851727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948349,0.00049181,0.00004795627,0.0004326169,0.0003999879,0.0002779032,0.001840941,0.0000470521,0.001626805],"genre_scores_gemma":[0.9833235,0.000305758,0.008062229,0.0008720224,0.0005567419,1.78493e-10,0.006736978,0.00003151234,0.0001112789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9451648,"threshold_uncertainty_score":0.9999005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04735029458685362,"score_gpt":0.2630055726534266,"score_spread":0.2156552780665729,"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."}}