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Fluoride inhibits root water transport and affects leaf expansion and gas exchange in aspen (<i>Populus tremuloides</i>) seedlings

2003· article· en· W2043883441 on OpenAlexafffund
Mohammed Kamaluddin, Janusz J. Zwiazek

Bibliographic record

VenuePhysiologia Plantarum · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFluoride Effects and Removal
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistrySodium fluorideRespirationStomatal conductancePhotosynthesisFluorideHydraulic conductivityHorticultureBotanyTranspirationBiologySoil waterInorganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

The effects of sodium fluoride (0.3, 5 and 10 mM NaF) on root hydraulic conductivity, and gas exchange processes were examined in aspen (Populus tremuloides Michx.) seedlings grown in solution culture. A long-term exposure of roots to NaF significantly decreased root hydraulic conductivity (Lp) and stomatal conductance ( gs). Root absorbed NaF significantly affected electrolyte leakage in leaf tissues and substantially restricted leaf expansion. NaF did not significantly affect leaf chlorophyll contents but decreased net photosynthesis (Pn). A short-term exposure of excised roots to 5 mM NaF and KF significantly decreased root water flow (Qv) with a concomitant decline in root respiration and reduced gs when applied through intact roots or excised stems. The same molar concentration of NaCl also decreased Qv and gs in intact seedlings, but to a lesser extent than NaF or KF, and did not significantly affect root respiration. The results suggest that fluoride metabolically inhibited Qv or Lp, probably by affecting water channel activity. We suggest that the metabolic inhibition of Lp by root-absorbed fluoride affected gas exchange and leaf expansion in aspen seedlings.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

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 head0.193
Teacher spread0.186 · 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 designBench or experimental
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

Citations59
Published2003
Admission routes2
Has abstractyes

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