Simulation of Pulse-Amplitude-Modulated (PAM) fluorescence: Limitations of some PAM-parameters in studying environmental stress effects
Bibliographic record
Abstract
Fluorescence parameters obtained during steady-state electron transport are frequently used to evaluate photosynthetic efficiency of plants. We studied the behaviour of those parameters as a function of irradiance-adapted fluorescence yields FS and F'M. Applied simulations showed that photochemical quenching evaluated by qP is greatly influenced by the steady-state fluorescence level (FS), and that its evolution is not complementary to non-photochemical quenching (qN). On the other hand, the relative photochemical and non-photochemical quenching coefficients (qP(rel) and qN(rel)) proposed by Buschmann (1995) represent better the balance between the energy dissipation pathways. However, these relative parameters are also non-linearly related when the FS level is varied. We investigated the application of a new parameter, the relative unquenched fluorescence (UQF(rel)) which takes into account the fraction of non-quenched fluorescence yield (FS), which is related to closed photosystem 2 reaction centres not participating in electron transport. By using computer simulations and real in vivo measurements, we found that this new parameter is complementary to qP(rel) and qN(rel), which may facilitate the use of PAM fluorescence as diagnostic tool in environmental studies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".