CO2 supply-demand coordination in photosynthesis when Rubisco and RuBP regeneration are co-limiting: supply & demand functions from Laisk dataset
Bibliographic record
Abstract
● Laisk method uses truncated A/Ci curves (demand function, DF) to estimate Ci* and Rd. In Laisk dataset, the Ca-Ci relationship reflects the supply function (SF), and points (Ci, A) for the same Ca can be fitted to a regression line (referred to Supply and Demand Function, DSF). ● The application of DSF to estimating Ci* and Rd by Laisk method and the relationship between DSF slope (dsf) and gs, and photosynthetic parameters were investigated in this study. ● Results showed that dsf was not affected by Laisk measurement conditions (PAR or Ca), while, it was inversely related to gs, apparent carboxylation efficiency (ACE) and apparent quantum yield (AQY). The dsf was essentially the slope of a light response curve (△A/△Ci-lrc) at low Ci. We devised an auxiliary line vertical to DSF and used it to improve the stability of Ci* and Rd estimates from Laisk data set for. ● We found that DSF slope was species-specific and independent of PAR and Ca. The dsf related CO2 diffusion to biochemical characteristics and represents the coordination between the two when Rubisco and RuBP regeneration co-limit photosynthesis. In conclusion, dsf can be used to describe the intrinsic characteristics of photosynthesis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".