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Record W2116175370 · doi:10.1080/09687680110096289

Considerations in measuring Potassium efflux from plant cells using 87 Rb magnetic resonance

2001· article· en· W2116175370 on OpenAlexaff
Marco L.H. Gruwel

Bibliographic record

VenueMolecular Membrane Biology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsPlant Biotechnology Institute
Fundersnot available
KeywordsPotassiumVacuoleEffluxRubidiumChemistryIon transporterBiophysicsBiochemistryCytoplasmMembraneBiology

Abstract

fetched live from OpenAlex

In order to stay metabolically active, plant cells must transport Potassium ions across their plasmalemma. Ion transport is subject to many complex metabolic regulatory processes. Information on Potassium metabolism can be obtained with 87Rb NMR spectroscopy, using Rubidium as a congener for Potassium. However, due to the presence of the vacuole, another non-metabolic mechanism for ion flux regulation exists. Using simple biophysical arguments, it is shown that an increase in vacuole size, without a change in total cell volume, could initiate a change in Potassium efflux. This change in efflux can be significant, especially for large vacuoles.

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)0.027
metaresearch head score (Gemma)0.026
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: Methods · Consensus signal: Methods
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.026
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0040.004
Open science0.0070.003
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0020.002

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 head0.031
GPT teacher head0.212
Teacher spread0.181 · 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
GenreMethods

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

Citations0
Published2001
Admission routes1
Has abstractyes

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