{"id":"W2897988501","doi":"10.1111/nph.15451","title":"Modelling carbon sources and sinks in terrestrial vegetation","year":2018,"lang":"en","type":"review","venue":"New Phytologist","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":310,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Center for Northern Studies","funders":"Stavros Niarchos Foundation; Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Carbon sink; Environmental science; Carbon cycle; Biosphere; Sink (geography); Primary production; Vegetation (pathology); Carbon fibers; Photosynthesis; Carbon sequestration; Atmospheric sciences; Ecology; Climate change; Ecosystem; Carbon dioxide; Computer science; Biology; Geography; Botany","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":[0.0002076052,0.0005334085,0.0003508255,0.0004856467,0.000307079,0.001052234,0.0004591932,0.0008412828,0.006118679],"category_scores_gemma":[0.0003517894,0.0003142629,0.0005604102,0.0005714227,0.0002574754,0.001000056,0.0008339118,0.0003934319,0.001369177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000731079,"about_ca_system_score_gemma":0.0007037676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003055687,"about_ca_topic_score_gemma":0.002301329,"domain_scores_codex":[0.9999498,0.00001250541,0.0000049358,0.0000125694,0.0000130617,0.000007053579],"domain_scores_gemma":[0.9999162,0.00003883876,0.00001003972,0.000006963122,0.00001631485,0.00001159789],"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":[0.00005698143,0.00002970242,0.002089526,0.001034138,0.00007170886,0.0001709912,0.0001542462,0.8520806,0.01043668,0.08026386,0.006426632,0.04718488],"study_design_scores_gemma":[0.00002784899,0.00006864864,0.003784932,0.0005351672,0.0000757251,0.0001556014,0.0001679637,0.6998087,0.005090155,0.1871294,0.1030911,0.00006481103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1616223,0.05564132,0.645218,0.005377902,0.001120414,0.0003493722,0.01275718,0.003719194,0.1141943],"genre_scores_gemma":[0.7806029,0.05104534,0.1221142,0.000492315,0.0005783114,0.0003914525,0.00702139,0.001032975,0.0367211],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.006118679,"threshold_uncertainty_score":0.02046907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04124636779203893,"score_gpt":0.2689348761471929,"score_spread":0.227688508355154,"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."}}