A new method for separate evaluation of PSII with inactive oxygen evolving complex and active D1 by the pulse-amplitude modulated chlorophyll fluorometry
Bibliographic record
Abstract
A method that separately quantifies the PSII with inactive oxygen-evolving complex (OEC) and active D1 retaining the primary quinone acceptor (QA )-reducing activity from the PSII with damaged D1 in the leaf was developed using PAM fluorometry. It is necessary to fully reduce QA to obtain F m , the maximum fluorescence. However, QA in PSII with inactive OEC and active D1 would not be fully reduced by a saturating flash. We used the acceptor-side inhibitor DCMU to fully reduce QA . Leaves of cucumber (Cucumis sativus L.) were chilled at 4°C in dark or illuminated with UV-A to selectively inactivate OEC. After these treatments, F v /F m , the maximum quantum yield, in the leaves vacuum-infiltrated with DCMU were greater than those in water-infiltrated leaves. In contrast, when the leaves were illuminated by red light to photodamage D1, F v /F m did not differ between DCMU- and water-infiltrated leaves. These results indicate relevance of the present evaluation of the fraction of PSII with inactive OEC and active D1. Several examinations in the laboratory and glasshouse showed that PSII with inactive OEC and active D1 was only rarely observed. The present simple method would serve as a useful tool to clarify the details of the PSII photoinhibition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".