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Record W2173826830 · doi:10.1139/cjb-2014-0032

Diel patterns of leaf carbohydrate concentrations differ between seedlings and mature trees of two sympatric oak species

2014· article· en· W2173826830 on OpenAlexvenueno aff
Ori Baber, Martijn Slot, Gerardo Celis, Kaoru Kitajima

Bibliographic record

VenueBotany · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersNational Science Council
KeywordsBiologyPhotosynthesisBotanySeedlingDiel vertical migrationEcophysiologySugarCarbohydrateCarbon dioxideEcology

Abstract

fetched live from OpenAlex

A fundamental aspect of the carbon cycle is the exchange of carbon between plants and the atmosphere. It is, therefore, important to understand factors that affect differences in gas exchange and carbon balance within and among species. Concentrations of nonstructural carbohydrates are often used as a proxy for carbon balance. We determined diel patterns of leaf carbohydrate concentrations in relation to irradiance (sun vs. shade) in seedlings and mature trees of two sympatric oak species (Quercus virginiana Mill. and Quercus hemisphaerica Bartram ex Willd.). For seedlings, we also measured leaf gas exchange. Higher sun exposure significantly increased photosynthesis and carbohydrate concentrations in both species. Carbohydrate concentrations of seedling leaves showed strong diel fluctuations, whereas concentrations in mature tree leaves did not. This contrast might be attributed to faster carbohydrate export from leaves of mature trees. The difference in sink strength between seedlings and adults may be related to the decreasing ratio of leaf mass to plant mass with ontogeny, increasing the demand for carbohydrates per unit leaf mass. Seedlings and mature trees are clearly functionally different and care must be taken when extrapolating results from seedling experiments to mature trees.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2014
Admission routes1
Has abstractyes

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