Analysis of global trends in scientific developments for the protection of fruit plants against frosts
Bibliographic record
Abstract
The main trends in scientific research on the protection of fruit plantations from spring frosts were analyzed based on the study of patent documentation of the countries of the world. China and the USA have the largest shares of patented developments by countries that have issued protection documents. The number of scientific studies on the mentioned problem and the patenting of their results increased significantly in the late 20th and early 21st centuries, confirming its relevance for world fruit growing. But in the 20s of the 21st century, the number of patents issued in the USA, Canada, Japan, Ukraine, as well as WIPO and EPO decreased significantly, while those issued in China increased several times. Among all methods of protecting orchards from frost, only 15 % were patented after 2010. For devices (protective shelters/screens, their designs), 48 % of protection documents were issued after 2010. After 2010, 42 % of patents were issued on devices for protecting plantations from frost, of which only 8 % are mobile. Among all means of protecting fruit plantations from frost, only 8 % were patented after 2010. Researchers have proposed different approaches to protecting plants from frost due to the wide variety of the distribution of the value of the temperature decrease indicator and their duration in most regions where fruit crops are grown. In recent decades, the improvement of previously developed methods and means, devices and devices for protecting fruit crops from frost, and their combination in various variants to improve protection, has been carried out. Systems for controlling weather conditions in plantations and controlling frost protection devices, both remote and automatic, were also created.
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 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 | 0.007 |
| Science and technology studies | 0.001 | 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".