{"id":"W2801277411","doi":"10.1093/treephys/tpy043","title":"Boreal tree hydrodynamics: asynchronous, diverging, yet complementary","year":2018,"lang":"en","type":"article","venue":"Tree Physiology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Wilfrid Laurier University; University of Saskatchewan; Université de Montréal; Global Institute for Water Security; Center for Northern Studies","funders":"ETH Zürich Foundation; Stavros Niarchos Foundation; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Black spruce; Boreal; Taiga; Larch; Ecology; Environmental science; Interspecific competition; Ecosystem; Atmospheric sciences; Biology; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001974616,0.0001219957,0.0001801417,0.0003387397,0.0001962985,0.0002761629,0.0001634474,0.0001317634,0.0002551222],"category_scores_gemma":[0.0002831614,0.000101649,0.0001058199,0.0001984024,0.0002354759,0.0002611891,0.0002858055,0.0001427184,0.00004792032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00020954,"about_ca_system_score_gemma":0.0001412748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004570479,"about_ca_topic_score_gemma":0.00818128,"domain_scores_codex":[0.9999185,0.00001365923,0.00000486167,0.00003227448,0.00001748182,0.00001313092],"domain_scores_gemma":[0.9998118,0.00002784087,0.00006917665,0.00001680319,0.00002729831,0.00004715116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002174251,0.0000821869,0.8125607,0.00005097507,0.00006128483,0.000176613,0.0006498835,0.0009987195,0.1596356,0.0004799672,0.000212974,0.02487364],"study_design_scores_gemma":[0.00000147074,0.00003004265,0.9985287,9.011735e-7,0.000004308604,0.00006321928,0.00007313267,0.0006591407,0.0004418571,0.00004820981,0.0001452093,0.000003714625],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988635,0.00009975514,0.0005657386,0.00001063087,0.000002497088,0.00000291427,0.00005620455,0.0000180646,0.0003808427],"genre_scores_gemma":[0.9995877,0.00002397,0.000246022,0.000005990591,0.000003356692,0.000002182036,0.00006265624,0.000002571241,0.0000656206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004570479,"threshold_uncertainty_score":0.009087741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007548666991861175,"score_gpt":0.217643153768306,"score_spread":0.2100944867764448,"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."}}