{"id":"W2535499357","doi":"10.1002/2016jg003440","title":"Climatic sensitivity, water‐use efficiency, and growth decline in boreal jack pine (<i>Pinus banksiana</i>) forests in Northern Ontario","year":2016,"lang":"en","type":"article","venue":"Journal of Geophysical Research Biogeosciences","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Forest Research Institute; Ministry of Natural Resources and Forestry; University of Guelph","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Boreal; Taiga; Climate change; Water-use efficiency; Precipitation; Photosynthetic capacity; Carbon dioxide; Photosynthesis; Growing season; Atmospheric sciences; Ecology; Forestry; Biology; Geography; Botany; Meteorology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00291645,0.0001349829,0.0002654296,0.0003255117,0.0001158736,0.0001158531,0.0003429508,0.00006557125,0.00002232022],"category_scores_gemma":[0.0003278354,0.00006951678,0.00006217766,0.0006844259,0.0008854219,0.0008184073,0.0004639152,0.0003878501,0.00004266636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003206322,"about_ca_system_score_gemma":0.0001043386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1580013,"about_ca_topic_score_gemma":0.7744192,"domain_scores_codex":[0.9971113,0.000271874,0.0004597623,0.0002984844,0.001195753,0.0006628188],"domain_scores_gemma":[0.9989546,0.0005133593,0.00009831161,0.0001406415,0.00006325193,0.0002298284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006149389,0.0002372648,0.9868621,0.000004327038,0.000002198839,0.0002307415,0.0003716874,0.00005609644,0.009170365,0.00009914771,0.00000931168,0.002895228],"study_design_scores_gemma":[0.0005488559,0.0004204072,0.988825,0.00008211321,0.000003061989,0.00007007951,0.00002318134,0.004139831,0.0005662264,0.005109617,0.00009608406,0.0001155017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977027,0.000009567407,0.0001875147,0.001631593,0.0000497536,0.0001347324,0.000008219178,0.000003510975,0.0002724305],"genre_scores_gemma":[0.9995406,0.00005306301,0.000180415,0.00003119758,0.0000291009,0.000002504653,0.000001519775,0.000005821807,0.0001557848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6164178,"threshold_uncertainty_score":0.8476056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949827358575754,"score_gpt":0.2652671139800636,"score_spread":0.245768840394306,"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."}}