Individual and interactive effects of temperature, carbon dioxide and abscisic acid on mung bean (<i>Vigna radiata</i>) plants
Bibliographic record
Abstract
We studied the effects of temperature, carbon dioxide and abscisic acid on mung bean (Vigna radiata). Plants were grown under 26/22°C or 32/28°C (16 h light/8 h dark) at 400 or 700 μmol mol−1 CO2 and received ABA application of 0 or 100 μl (10 μg) every other day for three weeks, after eight days of initial growth, in growth chambers. We measured 24 parameters. As individual factors, in 16 cases temperature; in 8 cases CO2; in 9 cases ABA; and as interactive factors, in 4 cases, each of temperature × CO2, and CO2 × ABA; and in 2 cases, temperature × ABA were significant. Higher temperatures increased growth, aboveground biomass, growth indices, photochemical quenching (qP) and nitrogen balance index (NBI). Elevated CO2 increased growth and aboveground biomass. ABA decreased growth, belowground biomass, qP and flavonoids; increased shoot/root mass ratio, chlorophyll and NBI; and had little role in regulating temperature–CO2 effects.Abbreviations: AN: net CO2 assimilation; E: transpiration; Fv/Fm: maximum quantum yield of PSII; gs: stomatal conductance; LAR: leaf area ratio; LMA: leaf mass per area; LMR: leaf mass ratio;φPSII: effective quantum yield of PSII; qNP: non-photochemical quenching; qP: photochemical quenching; SRMR: shoot to root mass ratio; WUE: water use efficiency
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".