{"id":"W2769056751","doi":"10.1007/s00484-017-1472-4","title":"Projections for the changes in growing season length of tree-ring formation on the Tibetan Plateau based on CMIP5 model simulations","year":2017,"lang":"en","type":"article","venue":"International Journal of Biometeorology","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Russian Science Foundation; Riksbankens Jubileumsfond; National Natural Science Foundation of China; Kungl. Vitterhets Historie och Antikvitets Akademien; Alexander von Humboldt-Stiftung","keywords":"Coupled model intercomparison project; Plateau (mathematics); Representative Concentration Pathways; Climate change; Climatology; Environmental science; Mean radiant temperature; Physical geography; Global warming; Growing season; Geography; Climate model; Mathematics; Ecology; Geology; Biology","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":[0.0007731738,0.00008599373,0.0001352417,0.000498785,0.0002473493,0.00007116864,0.000572793,0.00005387708,0.00005204846],"category_scores_gemma":[0.0005925629,0.00004950155,0.00008529529,0.00008419583,0.00009767525,0.0002941567,0.00001399028,0.0001536265,0.000003064379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002504165,"about_ca_system_score_gemma":0.00005855624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001407395,"about_ca_topic_score_gemma":0.003163162,"domain_scores_codex":[0.9990886,0.00008760031,0.0002872933,0.00008879422,0.0003052424,0.000142469],"domain_scores_gemma":[0.9971193,0.002043805,0.0004904305,0.0001652687,0.0001552612,0.0000259383],"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":[0.001829677,0.00008433876,0.04035171,0.00001163112,0.0001369656,0.000008475098,0.0004145348,0.8738619,0.002322695,0.001260815,0.00006278193,0.07965448],"study_design_scores_gemma":[0.0006356416,0.0004049896,0.1384003,0.00005834514,0.00002031539,0.0000165397,0.00009087966,0.857506,0.001831422,0.0006309917,0.0003535936,0.00005104368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9794328,0.00003693887,0.002660615,0.01643727,0.000564878,0.0001975757,0.0001626962,0.000005861094,0.0005013652],"genre_scores_gemma":[0.9990802,0.00002995454,0.0004662905,0.0002604456,0.0001267016,0.000002657683,0.00001276654,0.000003690973,0.00001733304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09804856,"threshold_uncertainty_score":0.2018615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05920687801045446,"score_gpt":0.310391718405053,"score_spread":0.2511848403945985,"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."}}