MétaCan
Menu
Back to cohort

Water movement between epidermal cells of barley leaves – a symplastic connection?

2000· article· en· W2038819260 on OpenAlexaboutno aff
Wieland Fricke

Bibliographic record

VenuePlant Cell & Environment · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsnot available
Fundersnot available
KeywordsTurgor pressurePlasmodesmaEpidermis (zoology)BiophysicsPlant cellApoplastWater flowCytoplasmic streamingSymplastChemistryXylemCell wallBotanyBiologyCell biologyAnatomyCytoplasmBiochemistryGeology

Abstract

fetched live from OpenAlex

ABSTRACT Using the cell‐pressure probe the possibility of symplastic water flow between cells of the upper epidermis of barley leaves was investigated. Cells analysed had either an intact or a more or less damaged cellular environment. Cell damage caused large pressure differentials (0·9 MPa) between damaged and adjacent intact cells. Turgor in cells adjacent to damaged cells decreased significantly. Turgor decreases were the larger the more the adjacent, damaged cell was leaking (decreases by 2·5–4·4%). In cells surrounded by a patch of leaking cells, turgor decreased the most, by 18·1–20·4%. In contrast, half‐times of water exchange (T1/2) of cells were not affected by a damaged cellular environment. Assuming that in the barley leaf epidermis, plasmodesmata close at pressure‐differentials at or exceeding 0·2 MPa as shown for other plant cells (The Plant Journal 2, 741–750; Canadian Journal of Botany 65, 509–511), it is concluded that symplastic water flow contributes insignificantly to water exchange between cells. Mechanical damage to one individual cell is enough to induce significant turgor changes in neighbouring cells.

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 score0.001
Threshold uncertainty score0.004

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 head0.003
GPT teacher head0.166
Teacher spread0.163 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

Explore more

Same venuePlant Cell & EnvironmentSame topicMagnetic and Electromagnetic EffectsFrench-language works237,207