{"id":"W2179138734","doi":"10.5194/gmd-9-2639-2016","title":"Integrating peatlands into the coupled Canadian Land Surface Scheme(CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0","year":2016,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Peat; Bog; Environmental science; Primary production; Ecosystem; Vegetation (pathology); Terrestrial ecosystem; Ecosystem respiration; Carbon cycle; Hydrology (agriculture); Atmosphere (unit); Atmospheric sciences; Carbon fibers; Physical geography; Ecology; Geology; Geography; Meteorology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00217785,0.0002921596,0.0002826243,0.00009669212,0.002038467,0.0002993894,0.0006676944,0.0001512656,0.0001270134],"category_scores_gemma":[0.00009289892,0.0001369079,0.00005835246,0.0002387198,0.0004529981,0.0001626974,0.0002588219,0.0001982375,0.0001170414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001165278,"about_ca_system_score_gemma":0.001199767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6132585,"about_ca_topic_score_gemma":0.9965664,"domain_scores_codex":[0.9974137,0.0001156974,0.0004562483,0.0006718278,0.0004432113,0.0008993028],"domain_scores_gemma":[0.9986609,0.0001159802,0.0001219941,0.0004854365,0.00002522488,0.0005904958],"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":[0.0006737417,0.0001637945,0.6648932,0.00007047639,0.0003790306,0.0001098612,0.05629998,0.110892,0.004670877,0.006659613,0.1151685,0.04001893],"study_design_scores_gemma":[0.001577899,0.00001255599,0.005188968,0.00003391976,0.0000156058,0.00001341178,0.0001236456,0.9497627,0.00004217014,0.0006397612,0.04226806,0.0003212849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843071,0.00004009309,0.004451652,0.00587216,0.0005446963,0.0006740144,0.00006130736,0.00004822285,0.004000818],"genre_scores_gemma":[0.9914579,0.00002112861,0.002490673,0.0003944199,0.00003836042,0.00008017789,0.0000565739,0.00002574898,0.005435064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8388707,"threshold_uncertainty_score":0.9992607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190741797110231,"score_gpt":0.1976003670339367,"score_spread":0.1856929490628344,"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."}}