{"id":"W4389455455","doi":"10.1007/s10021-023-00883-9","title":"Drainage-Driven Loss of Carbon Sequestration of a Temperate Peatland in Northeast China","year":2023,"lang":"en","type":"article","venue":"Ecosystems","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"National Natural Science Foundation of China","keywords":"Peat; Carbon sequestration; Environmental science; Drainage; Soil carbon; Carbon fibers; Hydrology (agriculture); Temperate climate; Biomass (ecology); Soil water; Ecology; Carbon dioxide; Soil science; Geology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003025591,0.00008399176,0.0002245395,0.0000760633,0.00002429536,0.000005356144,0.0001156492,0.0000618219,0.00008275327],"category_scores_gemma":[0.00001425086,0.00007212825,0.00003332993,0.0003307082,0.00004933524,0.00005814832,0.00005571463,0.00005795367,0.00003303102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005193937,"about_ca_system_score_gemma":0.00001248939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003899105,"about_ca_topic_score_gemma":0.01394421,"domain_scores_codex":[0.9991251,0.00007775021,0.0003064132,0.0001728797,0.0001361233,0.0001817049],"domain_scores_gemma":[0.9996611,0.00002298898,0.0001190749,0.0001548755,0.000005469269,0.00003641691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001360172,0.00003065067,0.9866304,0.00004310489,0.000005710518,0.00001997901,0.0006888482,0.002003879,0.01036529,0.00004537568,0.00008468832,0.00006850718],"study_design_scores_gemma":[0.0004739607,0.0001311803,0.9759236,0.00004508994,0.000004530189,0.000009516181,0.00008502551,0.02217381,0.0007296394,0.0001434799,0.0001895493,0.00009060745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875113,0.000006942745,0.000003845284,0.00007897167,0.000102135,0.0001848129,0.00001710083,0.00002064729,0.01207422],"genre_scores_gemma":[0.9996292,0.00001292343,0.000008730829,0.000002981692,0.00003124808,0.00001753019,0.00004109795,0.000007742805,0.0002485421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02016993,"threshold_uncertainty_score":0.7781198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00797441502063746,"score_gpt":0.2179650999840663,"score_spread":0.2099906849634288,"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."}}