CO<sub>2</sub> Demand-Supply Coordination in Photosynthesis Reflecting the Plant-Environment Interaction: Extension and Parameterization of Demand Function and Supply Function
Bibliographic record
Abstract
Photosynthesis consists of a biochemical process named demand and a CO2 diffusion process named supply function. The intersection (Ci, An) at equal to the demand function and the supply function reflects a steady state of the plant subjected to the environment. The intersections of these demand-supply functions under different photosynthetically active radiation (PAR) can be fitted to a regression line (names DSF) in which slope (ΔAn/ΔCi) can be defined as dsf. We found that DSF information was embedded in both Laisk method (CO2 response curve (A/Ci) measured at three sub-saturated PARs, and their intersections were used to estimate daytime respiration (Rd), and CO2 compensation point (Ci*) and light response curve measurements, which could be used to estimate dsf values. This study investigated the relationship between dsf and the parameters related to the biochemical process and the CO2 diffusion process of photosynthesis. The results showed that dsf was negatively correlated with gs, apparent carboxylation efficiency, and apparent quantum yield. This suggests that DSF may coordinate the influence of environmental conditions (light, CO2 and water) on photosynthesis in the biochemical and CO2 diffusion process. Moreover, dsf was independent of gas exchange measurement conditions and showed species specificity. In conclusion, we speculated that dsf seems to be a comprehensive parameter that might be related to the intrinsic adaptation mechanism of plants to environmental conditions. We proposed an auxiliary line perpendicular to the DSF and used it to improve the stability of Ci* and Rd estimated from the Laisk dataset.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".