{"id":"W3118097547","doi":"10.3390/f12010012","title":"Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models","year":2020,"lang":"en","type":"article","venue":"Forests","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"National Natural Science Foundation of China","keywords":"Primary production; Environmental science; Climate change; Radiative forcing; Plateau (mathematics); Climatology; Ecosystem; Forcing (mathematics); Terrestrial ecosystem; Climate model; Global change; Carbon cycle; Representative Concentration Pathways; Atmospheric sciences; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002873748,0.0001505945,0.0001797333,0.00004874,0.000138492,0.00004873161,0.0003730628,0.00006679184,0.00002952594],"category_scores_gemma":[0.00005281325,0.00008347249,0.0001129752,0.0004586207,0.00007496063,0.0001670505,0.00007403854,0.0001429939,0.00001207025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005840765,"about_ca_system_score_gemma":0.000005647445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001733185,"about_ca_topic_score_gemma":0.004346878,"domain_scores_codex":[0.9986744,0.0001528963,0.0002376715,0.0002991135,0.0003874219,0.0002485339],"domain_scores_gemma":[0.9990979,0.0002359426,0.0001441099,0.0004304736,0.000004398213,0.00008719922],"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":[0.0001192389,0.00007139784,0.1022016,0.000002817975,0.00001867043,0.000003754026,0.000707488,0.8962442,0.0003014829,0.000174419,0.00001145768,0.0001434895],"study_design_scores_gemma":[0.0002599852,0.0001905727,0.0300162,0.00001774623,0.00007317195,4.484222e-7,0.00002393962,0.9689718,0.0002302449,0.00004671233,0.00006424955,0.0001049309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979964,0.000003489378,0.0002029111,0.0005505202,0.00008987817,0.0004431186,0.0001705982,0.00003102517,0.0005120148],"genre_scores_gemma":[0.9995865,0.000005290843,0.00002110746,0.0002037245,0.00005873268,0.00003290046,0.00007016279,0.00001313842,0.000008455097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07272764,"threshold_uncertainty_score":0.340391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04045626617248121,"score_gpt":0.2259069503984834,"score_spread":0.1854506842260021,"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."}}