{"id":"W4380680678","doi":"10.3389/ffgc.2023.1181653","title":"Strong latitudinal gradient in temperature-growth coupling near the treeline of the Canadian subarctic forest","year":2023,"lang":"en","type":"article","venue":"Frontiers in Forests and Global Change","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick; University of Toronto; Center for Northern Studies; Université Laval","funders":"Royal Canadian Geographical Society; Natural Sciences and Engineering Research Council of Canada; Ministère des Forêts, de la Faune et des Parcs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Subarctic climate; Biome; Taiga; Environmental science; Precipitation; Boreal; Climate change; Climatology; Tree line; Atmospheric sciences; Black spruce; Latitude; Physical geography; Ecology; Ecosystem; Geography; Geology; Biology","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":[0.0003159113,0.0001101133,0.0001509804,0.00009694253,0.0002564195,0.00007562157,0.0002256185,0.00006574652,0.000009005194],"category_scores_gemma":[0.00007220592,0.0000658278,0.00003571828,0.0007466048,0.0002268803,0.00008951999,0.00002482994,0.0001413768,0.000003430088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003980564,"about_ca_system_score_gemma":0.0001236517,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4020354,"about_ca_topic_score_gemma":0.9898258,"domain_scores_codex":[0.9990516,0.00004014949,0.0001605867,0.0001698951,0.0001858378,0.0003919068],"domain_scores_gemma":[0.9996579,0.00004761997,0.0000446414,0.0001382067,0.00001840755,0.00009324235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003508719,0.000003721859,0.9961545,0.00002042414,0.000006197725,0.00001944927,0.0002643495,0.001896108,1.016456e-7,0.0003969564,0.0005719396,0.0006311057],"study_design_scores_gemma":[0.0002199964,0.00004086737,0.9679287,0.00005708389,0.000006998513,0.000004770083,0.0002583163,0.02997429,8.00029e-7,0.000875678,0.0005589795,0.00007352291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957603,0.001283914,8.100558e-7,0.001696103,0.0005313247,0.0002655602,0.0002165186,0.00001121144,0.0002343103],"genre_scores_gemma":[0.9996532,0.0001165131,0.00004807294,0.00007149461,0.00005286276,0.000004341221,0.00003216956,0.000003013135,0.00001835047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5877904,"threshold_uncertainty_score":0.6019465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585702781230731,"score_gpt":0.2341629538737694,"score_spread":0.2083059260614621,"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."}}