Bibliographic record
Abstract
The different physiological parameters viz.chlorophyll, carotenoids, carbohydratrates, proteins and micro nutrients concentrations of Lycopersicon esculentum were observed under different salt concentrations from control (non-saline), 60mM NaCl and 100mM NaCl solutions.The rates of different physiological parameters and micro nutrients' concentrations exhibited decreases in saline media in comparison with their respective controls while brassinosteroids were used exogenously as a foliar spray and in roots at the concentration of 0.25 ppm and 0.50 ppm, and showed a promotion in the non-saline control when compared to salt concentrations' media.In physiological parameters analysis i.e.Chlorophyll a, Chlorophyll b, Chlorophyll a/b ratio, total chlorophyll, carotenoids, total carbohydrates and total proteins were studied and treated against different NaCl concentrations i.e. 60 and 100mM.Salt concentrations showed an increase in NaCl media compared to their controls, while plants treated with brassinosteroids at 0.25 ppm and 0.50 ppm, which were applied as a foliar spray and in roots, showed an increase in all physiological parameters analysis in control and at 60mM NaCl concentration.Amongst the micro nutrients, the ionic composition i.e.Na, K and Na/K ratio showed that plants treated with different NaCl concentrations at 60mM NaCl and 100mM salt concentrations showed an increase in Na and K ions, and brassinosteroids applied exogenously as a foliar spray and in roots showed a decrease in Na and K ions.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.907 | 0.930 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".