Can unidirectional influx be measured in higher plants? A mathematical approach using parameters from efflux analysis
Bibliographic record
Abstract
Summary A comprehensive and pragmatic approach to the design of unidirectional ion transport experiments in plants is presented here, revising and simplifying classical models. The kinetic constant for cytosolic ion exchange ( k c ) is critical to the understanding of the interrelated flux processes occurring simultaneously at the cellular level. This constant is most effectively estimated using the compartmental analysis by efflux method, which, by providing values for additional kinetic parameters (i.e. unidirectional influx and efflux) can be used to determine the extent of distortion inherent in assessments of influx at, or close to, the steady state. Focusing on the kinetics of nitrogen exchange, with tracer efflux experiments in barley ( Hordeum vulgare ) using 13NH4+, conducted under perturbation conditions, it was demonstrated that a transitional state was rapidly established following a concentration shift, characterized by a restoration of the preperturbational (steady‐state) kc value. It is concluded that a reasonably accurate estimate of unidirectional influx can be made when influx measurements are conducted subsequent to the establishment of this transitional state. A mathematical treatment of unidirectional flux processes allows the exact determination of errors caused by ionic counterfluxes under steady‐state conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".