{"id":"W2965069693","doi":"10.1007/s10661-019-7639-1","title":"A 1-year greenhouse gas budget of a peatland exposed to long-term nutrient infiltration and altered hydrology: high carbon uptake and methane emission","year":2019,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"Greenhouse gas; Environmental science; Infiltration (HVAC); Peat; Methane; Hydrology (agriculture); Nutrient; Carbon dioxide; Ecology; Geology; Geography; 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":[0.0001932494,0.0002026418,0.0002795891,0.00005376765,0.0000785885,0.00002374708,0.00007574189,0.00009716581,0.00008286178],"category_scores_gemma":[0.000003854804,0.0001777815,0.0000234564,0.00004894311,0.0001030422,0.0001009133,0.0002689481,0.0001403122,0.000004545764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020875,"about_ca_system_score_gemma":0.000005319235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001437305,"about_ca_topic_score_gemma":0.00001086052,"domain_scores_codex":[0.9987269,0.00006427112,0.0002542005,0.0004575585,0.0002346098,0.000262472],"domain_scores_gemma":[0.999445,0.00004597016,0.000104193,0.0001971212,0.000001431192,0.0002062674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006520958,0.00009850742,0.7632785,0.00001521147,0.00001569408,0.00000527407,0.0002234099,0.00002233292,0.2321582,0.000003679233,0.000005660883,0.004108364],"study_design_scores_gemma":[0.00150001,0.001064188,0.9771622,0.00003714809,0.00003223097,0.00002047917,0.0001215332,0.0001601358,0.01949115,0.00005019592,0.0001712979,0.0001894254],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988641,0.0001015388,0.00002154796,0.0001245465,0.0001758072,0.0004587209,0.00001125723,0.00001562771,0.0002268832],"genre_scores_gemma":[0.9983853,0.0005508074,0.000750812,0.00002057646,0.00007351955,0.00004287598,0.00002306287,0.00001649949,0.0001366196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2138837,"threshold_uncertainty_score":0.7249718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008327950396218831,"score_gpt":0.2387697881260108,"score_spread":0.2304418377297919,"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."}}