Effects of microbial agents and corn protein ferment on physiological characteristics in leaves and yield of tomato.
Bibliographic record
Abstract
), chlorophyll (a+b) content, net photosynthetic rate, and the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) in leaves increased by 16.4%, 30.9%, 23.4%, 33.0% and 40.3%, respectively, compared with the CK. Furthermore, plant height and stem diameter increased by 8.2% and 7.0%, while the total yield exhibited a significant increase of 9.9% compared with the CK 210 days post-treatment. In conclusion, the combined application of microbial agents and corn protein ferment has promising potential in enhancing chlorophyll content, net photosynthetic rate, and the activities of SOD, POD and CAT in tomato leaves. This approach effectively delayed leaf senescence, thereby promoting tomato growth and remarkably increasing the yield.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".