{"id":"W2152051327","doi":"10.1093/treephys/27.5.703","title":"Improved simulation of poorly drained forests using Biome-BGC","year":2007,"lang":"en","type":"article","venue":"Tree Physiology","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Environmental Biology; Goddard Space Flight Center; National Aeronautics and Space Administration; University of Montana; National Science Foundation","keywords":"Environmental science; Primary production; Biome; Soil water; Peat; Bryophyte; Evergreen; Taiga; Hydrology (agriculture); Biogeochemical cycle; Wetland; Biomass (ecology); Ecology; Ecosystem; Soil science; Biology; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006800992,0.0008622795,0.0006679387,0.0004442722,0.0004878571,0.001036957,0.001140061,0.0009633825,0.001405307],"category_scores_gemma":[0.001580792,0.0003892601,0.0005608564,0.0005966088,0.00046062,0.0005333806,0.0006069231,0.0006960174,0.0001326996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001563093,"about_ca_system_score_gemma":0.001955382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08762038,"about_ca_topic_score_gemma":0.05243804,"domain_scores_codex":[0.9998043,0.00005665289,0.00001592989,0.0000476048,0.00003401214,0.00004150628],"domain_scores_gemma":[0.9992564,0.0003291035,0.00006177776,0.0000721999,0.0001641175,0.0001162649],"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":[0.00006855061,0.00006974763,0.008534005,0.00001420855,0.00002634012,0.00003751481,0.00002546973,0.9877619,0.001274506,0.0004278901,0.0002729499,0.001486985],"study_design_scores_gemma":[0.00002781108,0.00001069652,0.001145009,0.000001592404,0.000005869769,0.000004956213,0.000007491321,0.9981536,0.0002908921,0.0001184913,0.0002291572,0.000004493616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800606,0.00008322568,0.01248737,0.0001896025,0.0000468144,0.00005530486,0.001891919,0.0009141333,0.004271027],"genre_scores_gemma":[0.9883709,0.00005258902,0.009769239,0.00004596732,0.000007380374,0.00005067871,0.001195878,0.00007156091,0.000435784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08762038,"threshold_uncertainty_score":0.1742207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631696508513212,"score_gpt":0.2741415995228885,"score_spread":0.2578246344377564,"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."}}