INVESTIGATION OF THE HYDRAULIC DRIVE OF THE UNIT FOR STRIP TILLAGE WITH SIMULTANEOUS APPLICATION OF LIQUID FERTILIZERS
Bibliographic record
Abstract
One of the most difficult issues at present is the land market. In the political direction, there is an extensive discussion about the land market, but almost no one raises the issue of its preservation for future generations. Many scientists, especially soil scientists, warn of the gradual loss of its fertile potential due to a sharp decrease in the soil of the main indicator fertility - humus. As a result of conducting intensive technologies in crop production in the agro-industrial complex, the main purpose of which is to obtain large profits, the recommended crop rotations are not followed, as crops such as wheat, corn, soybeans and sunflowers are grown. With this attitude to the land, it will lose fertility in the near future, due to a sharp drop in humus. In many publications of soil scientists over the past 20 years, humus has decreased by almost 2% on average, while in the previous 100 years it has decreased by 1.5-2%. Thus, it is urgent to change the adopted technology to soil-preserving, which, along with the preservation of the soil with their proper implementation are not inferior to the yield of industrial technologies. It is necessary to pay attention to how energy and soil-saving technologies are used in most countries of America, Canada, and Europe. These are No-Till and Strip-till technologies. These technologies are based on minimal tillage with mandatory high-quality soil cover with crop residues. The technology is complex and requires proper implementation in the presence of appropriate machines. In Vinnytsia National Agrarian University has developed a design of units most accessible to farms Strip-till strip tillage technologies.
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 | 0.001 |
| 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) | 0.002 | 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".