{"id":"W2804435956","doi":"10.1038/s41598-018-26147-4","title":"Peatland vegetation composition and phenology drive the seasonal trajectory of maximum gross primary production","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Svenska Forskningsrådet Formas; Vetenskapsrådet; Kempe Foundation","keywords":"Primary production; Abiotic component; Environmental science; Peat; Phenology; Vegetation (pathology); Atmospheric sciences; Biomass (ecology); Ecology; Ecosystem; Carbon cycle; Boreal; Biology; Geology","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":[0.0002204348,0.0001277437,0.000152632,0.0002159624,0.0001199601,0.0003129755,0.00009418495,0.0001133542,0.0005115601],"category_scores_gemma":[0.0003559988,0.0001115853,0.0001348671,0.0001633894,0.000135501,0.0002214766,0.000199306,0.0001110308,0.0001107771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00017882,"about_ca_system_score_gemma":0.0002176847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006230241,"about_ca_topic_score_gemma":0.01072313,"domain_scores_codex":[0.9999608,0.000008869232,0.000002002707,0.00001418016,0.000004527947,0.000009640561],"domain_scores_gemma":[0.9998277,0.00004311497,0.00004687751,0.00001137417,0.00002594655,0.00004495184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002635495,0.00007529082,0.8235829,0.00006961436,0.00009806831,0.000146866,0.0002243008,0.007075054,0.150477,0.0004781675,0.0002512587,0.01725779],"study_design_scores_gemma":[0.000001647763,0.0000197023,0.9914978,0.000003645104,0.000007550066,0.0000257254,0.00006153871,0.006811725,0.001235156,0.0001667562,0.0001647936,0.000003925756],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990475,0.00005848837,0.0005578058,0.000008470628,0.000001508847,0.000001738339,0.0001042302,0.00001082766,0.0002094012],"genre_scores_gemma":[0.9996332,0.00001956118,0.0002138175,0.000001866974,6.480705e-7,0.000001369629,0.00006205548,0.000002890446,0.00006462738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006230241,"threshold_uncertainty_score":0.01238793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007642819723905581,"score_gpt":0.2127162098329184,"score_spread":0.2050733901090128,"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."}}