THE IMPACT OF MARS EL GROWTH REGULATOR ON THE YIELD OF CARROTS
Bibliographic record
Abstract
Studies have shown, that the laboratory germination of carrot seeds after soaking in Mars EL solution increased by 13% in Abaco hybrid, and by 12% in Canada hybrid, and field germination by 9% and 10%, respectively. Under the action of Mars EL growth regulator the number of leaves increased on average by 2-3 pcs. per carrot in Abaco hybrid, and 2-4 pcs. in Canada hybrid. The highest yield in the experiment was provided by the use of Mars EL for soaking seeds and spraying plants three times during the growing season. On average, in three years of research, 48.4 t / ha were obtained in the areas, where Abaco hybrid was grown, and 52.0 t / ha in the areas, where Canada hybrid was grown. In the same case due to the use of Mars EL growth regulator the marketability of carrot roots increased by 6-7%. .
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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".