The Use of a Time-Changing Magnetic Field to Increase Soybean (Glycine max) Growth and Productivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aimed to accelerate the growth and increase the productivity of soybean plants by providing treatment using a magnetic field at the time of seed germination. The research sample was soybean seeds of the Grobogan variety obtained from Center for Research on Various Tubers and Nuts. The magnetic field used in the treatment is in the direction of the magnetic flux density, which changes with time, and the change frequency is 100 times per second. The treatments were given with magnetic flux density from 0.0 mT to 0.5 mT for 20 minutes per day and repeated for five days. Treatment with a 0.1 mT magnetic field resulted in optimum values of germination emergence time, stem growth, chlorophyll content, early flowering time, weight per 10 seeds, and productivity. Treatment with a 0.5 mT magnetic flux density had a negative or no effect on the growth and productivity of soybean plants. Treatment using a magnetic field of 0.1-0.4 mT positively affected soybean growth and productivity, while 0.5 mT did not affect or negatively affect. The treatment of the magnetic field can have positive and negative effects depending on the magnetic flux density used.
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.
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 it