{"id":"W4300891176","doi":"","title":"Modelling tree ring cellulose δ18O variations in two temperature-sensitive tree species from North and South America","year":2017,"lang":"en","type":"preprint","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Université du Québec à Montréal","funders":"Climate Program Office; Natural Resources Canada; Office of Science; Aix-Marseille Université; National Oceanic and Atmospheric Administration; Biological and Environmental Research; European Commission; U.S. Department of Energy","keywords":"Dendrochronology; Tree (set theory); Cellulose; Ring (chemistry); Forestry; δ18O; Geography; Chemistry; Mathematics; Combinatorics; Archaeology; Physics; Organic chemistry; Nuclear physics; Stable isotope ratio","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":[0.0002549602,0.0005064073,0.000304606,0.0003324772,0.0003940007,0.0005070205,0.0007129894,0.0008276642,0.0005698419],"category_scores_gemma":[0.0006962452,0.0003598028,0.0006844606,0.0004890003,0.0002857565,0.0004126876,0.0002922941,0.0003369082,0.00007319647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107793,"about_ca_system_score_gemma":0.0008975604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.130266,"about_ca_topic_score_gemma":0.1406107,"domain_scores_codex":[0.9999291,0.00001468971,0.000003361936,0.00003108798,0.000006598259,0.0000152511],"domain_scores_gemma":[0.9997361,0.0001303923,0.00004516221,0.00002069618,0.00003743265,0.00003020215],"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":[0.0002102058,0.0001267475,0.1278919,0.00007949847,0.0001494539,0.0002445726,0.0002851351,0.8504852,0.01387921,0.0003557523,0.0002591614,0.006033137],"study_design_scores_gemma":[0.00004891581,0.0000555006,0.07502005,0.000009404472,0.00004602469,0.00005258737,0.0001586822,0.9226864,0.001357965,0.0001593253,0.0003833045,0.00002188376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990605,0.00003024248,0.0004833681,0.00002084462,0.000001480115,0.000004613299,0.0001083669,0.00001279441,0.0002778056],"genre_scores_gemma":[0.9982527,0.00004937666,0.001235064,0.000009564227,0.000001591864,0.00001407804,0.0002599602,0.00001118431,0.0001664348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.130266,"threshold_uncertainty_score":0.2590155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040884543675773,"score_gpt":0.2387955945549501,"score_spread":0.2083867491181924,"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."}}