COMPARATIVE HYGIENIC ASSESSMENT AND ANALYSIS OF THE RANGES AND SCOPE OFF PESTICIDES IN DIFFERENT COUNTRIES
Bibliographic record
Abstract
Relevance. The task of maximizing the resource potential of agriculture is facing all countries of the world, including Ukraine. Pesticides allow farms to increase their efficiency, increase yields and reduce losses from harmful factors. Objective: analysis and hygienic assessment of the quantitative use and volume of use of different classes of pesticides in the world. Materials and methods. The object of our research was the range and scope of pesticides used in our countries; factors influencing and the use of different classes of pesticides. Results. Ukraine ranks first in Europe in terms of sown areas among the countries we study – 72% of the total area of the state. Jamaica has the largest number of drugs, their number is 3791 pesticides. In the structure of the range of chemical plant protection products Australia, Canada and Ukraine include 3248 pesticides, 3025 pesticides and 893 pesticides, respectively. The highest rate of pesticide use in the United States is 373 kg per 1 hectare of field, in Ukraine it is only 2 kg per 1 hectare of sown area (the last place among the countries we studied). New generations of plant growth regulators are being introduced into world agriculture, which will increase the gross harvest of the main food crops by 15-20 %. The predominant producers of chemical plant protection products (according to our estimates in 2018) in Ukraine are China – 42%, own production – 12%, Switzerland – 8%, Germany – 7% and others. Conclusion. The use of plant chemicals is an integral part of modern world agriculture. The volume, quantity and range of pesticides in the countries of the world we study depend on many factors. Among them: territorial location, climatic and weather conditions, level of economic development, etc.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".