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Record W2974049870 · doi:10.1002/ajb2.1360

The onset of xylogenesis in Smith fir is not related to outer bark thickness

2019· article· en· W2974049870 on OpenAlexaff
Xiaoxia Li, Sergio Rossi, Eryuan Liang

Bibliographic record

VenueAmerican Journal of Botany · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité du Québec à Chicoutimi
FundersChina Postdoctoral Science Foundation
KeywordsBiologyBark (sound)Douglas firBotanyEcology

Abstract

fetched live from OpenAlex

PREMISE: The resumption of stem growth varies across the ontogenetic development of trees. Compared with younger trees, older ones have thicker outer bark with a temperature-insulating effect that could potentially prevent the stem from warming in the spring. However, the question of whether xylogenesis in old trees is influenced by the thick bark still remains unresolved. METHODS: We investigated the onset of xylogenesis across the ontogenetic development of Smith fir (Abies georgei var. smithii) trees in the Sygera Mountains, southeastern Tibetan Plateau. The outer bark of older trees was also removed. Xylogenesis was monitored in microcores we collected every 3 days during May and June in 2017. RESULTS: Xylogenesis began in late May in young (<50 yr) and mature (50-100 yr) trees, 1 week earlier than in adult (>100-150 yr) and old (>150-200 yr) trees. Older (>200 yr) trees had the latest onset of xylogenesis, 2 weeks after young trees. The resumption of xylogenesis was similar between the control and bark-removed trees. CONCLUSIONS: Growth resumption was delayed in older and bigger trees. Outer bark did not affect the onset of xylogenesis, which indicated that the delayed resumption of growth during the lifespan of trees could be more related to endogenous factors than to an insulating effect of the thick bark of older individuals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.231
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2019
Admission routes1
Has abstractyes

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