{"id":"W2135669037","doi":"10.1029/2011jg001836","title":"Incorporating spatial heterogeneity created by permafrost thaw into a landscape carbon estimate","year":2012,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Permafrost; Tundra; Thermokarst; Eddy covariance; Ecosystem respiration; Environmental science; Ecosystem; Atmospheric sciences; Physical geography; Primary production; Soil carbon; Hydrology (agriculture); Ecology; Soil science; Soil water; Geology; Geography","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":[0.001090377,0.0004101533,0.0004054787,0.001691062,0.0002691066,0.0007754712,0.0004982817,0.0004768748,0.0005243389],"category_scores_gemma":[0.00304187,0.0003336247,0.0007685236,0.001078297,0.0002203947,0.0008844252,0.0006063235,0.0002226041,0.0001061953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006830986,"about_ca_system_score_gemma":0.000346705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01642135,"about_ca_topic_score_gemma":0.02731123,"domain_scores_codex":[0.9996686,0.00009496151,0.00002983802,0.0001254152,0.00004660876,0.0000345948],"domain_scores_gemma":[0.999061,0.0004200769,0.0001652387,0.0001247661,0.0001857037,0.000043279],"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":[0.00006287188,0.00004097274,0.5348095,0.00004415859,0.0004027044,0.0001560806,0.00009504704,0.4269366,0.004008224,0.00123839,0.00035085,0.03185462],"study_design_scores_gemma":[0.00001228508,0.00001801298,0.1665193,0.00001264996,0.00005465262,0.0000977144,0.00006479485,0.8303464,0.0007710648,0.001383379,0.0006949852,0.00002469747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9377283,0.0002292882,0.05905519,0.0001178789,0.00000884805,0.00002555426,0.001144679,0.000339965,0.001350354],"genre_scores_gemma":[0.9897473,0.00003371191,0.009626354,0.00001564276,0.000004280238,0.00001185112,0.0004602769,0.00001893819,0.00008177372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01642135,"threshold_uncertainty_score":0.03265154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04820235138380372,"score_gpt":0.3280828380749907,"score_spread":0.2798804866911869,"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."}}