{"id":"W4402931552","doi":"10.5194/egusphere-2024-2802","title":"Modelling decadal trends and the impact of extreme events on carbon fluxes in a deciduous temperate forest using the QUINCY model","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Toronto Metropolitan University","funders":"Academy of Finland","keywords":"Temperate deciduous forest; Deciduous; Environmental science; Temperate climate; Temperate forest; Temperate rainforest; Atmospheric sciences; Climatology; Ecology; Geology; Biology; Ecosystem","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008345521,0.0007025734,0.0004480001,0.0005227654,0.0004700345,0.0009685978,0.00121357,0.0008694623,0.001712808],"category_scores_gemma":[0.001477034,0.0003492398,0.000844807,0.0005909554,0.0004195251,0.0005720929,0.0004920688,0.0007704757,0.0001339932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377655,"about_ca_system_score_gemma":0.0009976266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1647447,"about_ca_topic_score_gemma":0.08988035,"domain_scores_codex":[0.9998546,0.00004356612,0.000008002332,0.00004853829,0.00001485185,0.00003038211],"domain_scores_gemma":[0.9994953,0.0002392424,0.00006449233,0.00003786896,0.0001000727,0.00006300539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009780841,0.0000353422,0.0228048,0.00002656892,0.00007952995,0.00007025492,0.00002488625,0.9733739,0.0005985055,0.0006531012,0.0005366537,0.001698477],"study_design_scores_gemma":[0.00001797125,0.00001143281,0.004091223,0.000003085701,0.00001515165,0.000008113266,0.00001171787,0.9953964,0.0001021377,0.0001354444,0.0002010535,0.000006255591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878127,0.0002187256,0.006480424,0.0002981076,0.00003705265,0.00002105542,0.00182825,0.0002980027,0.003005766],"genre_scores_gemma":[0.9964779,0.00007664401,0.002080992,0.00004482589,0.000008977112,0.00002309586,0.0008143317,0.00003411641,0.0004389903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1647447,"threshold_uncertainty_score":0.3275715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02911257928612356,"score_gpt":0.26136315205734,"score_spread":0.2322505727712164,"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."}}