{"id":"W2293234679","doi":"10.5194/tc-10-1721-2016","title":"Evaluation of air–soil temperature relationships simulated by land surfacemodels during winter across the permafrost region","year":2016,"lang":"en","type":"article","venue":"The cryosphere","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China; European Commission; Department for Environment, Food and Rural Affairs, UK Government; Agence Nationale de la Recherche; Met Office; National Science Foundation","keywords":"Permafrost; Snow; Environmental science; Northern Hemisphere; Snowmelt; Vegetation (pathology); Snow cover; Hydrology (agriculture); Atmospheric sciences; Soil science; Geology; Geotechnical engineering; Geomorphology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001159581,0.000169586,0.0001539843,0.000009322658,0.0005631362,0.00006231258,0.000280208,0.0001502102,0.003118871],"category_scores_gemma":[0.00005572194,0.00007759372,0.0000798803,0.0001997731,0.000158072,0.0002659152,0.0000247837,0.0002235787,0.0002080586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001750617,"about_ca_system_score_gemma":0.00004163083,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001391229,"about_ca_topic_score_gemma":0.05698736,"domain_scores_codex":[0.9982067,0.0004242634,0.0002614099,0.0002467418,0.0005524497,0.0003084438],"domain_scores_gemma":[0.9987817,0.0003704576,0.000139145,0.000415595,0.0002298617,0.00006328362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001096431,0.00001645726,0.968083,0.0000181929,0.00004216118,0.000002511214,0.002787708,0.01684417,0.004372086,0.000001842989,0.005214985,0.002507203],"study_design_scores_gemma":[0.00115224,0.00005094408,0.9783476,0.0001266754,0.00008575434,0.00002786686,0.001013471,0.01542233,0.0007761191,0.0003216498,0.002445579,0.0002297875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931104,0.001687293,0.000009028402,0.00157958,0.0002261808,0.0003200588,0.002285322,0.00002510816,0.0007570456],"genre_scores_gemma":[0.9963718,0.000141563,0.000001506403,0.0001252279,0.0001273169,0.000002419053,0.0004686571,0.000009386796,0.002752134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05559613,"threshold_uncertainty_score":0.9977924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0452216727415034,"score_gpt":0.2585486918973537,"score_spread":0.2133270191558503,"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."}}