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Record W2120720022 · doi:10.1139/cjb-2013-0121

Winter and summer leaves of <i>Cistus incanus</i>: differences in leaf morphofunctional traits, photosynthetic energy partitioning, and poly(ADP-ribose) polymerase (PARP) activity

2013· article· en· W2120720022 on OpenAlexvenueno aff
Carmen Arena, Veronica De Micco, Anna De Maio, Carmela Mistretta, Giovanna Aronne, Luca Vitale

Bibliographic record

VenueBotany · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsnot available
FundersNational Institutes of HealthUniversity of Oxford
KeywordsPhotosynthesisBiologyBotanyPoly ADP ribose polymeraseRuBisCOChloroplastHorticultureChlorophyllPolymeraseBiochemistryDNA

Abstract

fetched live from OpenAlex

Leaf anatomy, photosynthetic performance, and the role of poly(ADP-ribosyl)ation in maintaining genomic stability in winter and summer leaves of Cistus incanus L. were investigated to evaluate the strategies allowing this species to grow in a Mediterranean climate. Measurements on summer leaves (SL) were conducted at midday and on the following morning to assess the reversibility of changes induced by high temperatures and irradiances reached at midday. Winter leaves (WL) were thicker with a lower leaf density and higher intercellular spaces compared with SL, which showed reduced net photosynthesis (P n ) and a decrease in Rubisco activity. Compared with WL, SL showed a higher thermal dissipation (Φ NPQ ) in compensating for the reduced P n . This allowed minimization of ROS production (low Φ NO ) and hence prevented photo-oxidative damage. In SL, poly(ADP-ribose) polymerase (PARP) activity was down-regulated, probably allowing leaves to become tolerant to high temperatures and irradiances. SL are also characterised by chloroplasts occupying larger cell volume and well exposed to intercellular spaces. This may well favour better liquid-phase CO 2 diffusion towards carboxylation sites, contributing to reducing the negative influence of high leaf density and the low percentage of intercellular spaces on photosynthesis.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.190
Teacher spread0.176 · 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
Published2013
Admission routes1
Has abstractyes

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