Breeding of the herbifagic insect<em> Tarachidia candefacta</em> Hubn. on an artificial nutrient medium to suppress the development of Ambrosia artemisiifolia L plants
Bibliographic record
Abstract
Ragweed (Ambrosia artemisiifolia L.) is an invasive plant species from the American continent, which has actively penetrated plant communities, displacing local species of cultivated and weed vegetation. The uncontrolled development and widespread distribution of ragweed in the South of Russia are associated with the absence of natural enemies of this weed. Ragweed is not only a competitor of cultivated and weed plants but also causes allergic diseases. The ragweed moth (Tarachidia candefacta Hbn.) was imported from Canada as a biological agent to control ragweed's development and distribution. We used the mass release of herbiphage into agrocenoses during the emergence of ragweed, which implies an artificial shift in the phenophase of the bioagent, which was achieved by early mass dilution on an artificial nutrient medium (ANM) under laboratory conditions. To cultivate the ragweed moth, the ANM was improved by adding powdered milk as a source of protein and vitamins to the composition, which made it possible to improve the quality of the environment and improve the biological indicators of the development of the bioagent. Replacement of wheat germ with soybean meal in ANM made it possible to obtain a feed balanced in protein and amino acid composition for growing herbiphage. As a result of the research, a method of colonization of the ragweed moth was developed, based on the early mass cultivation of herbiphage on an improved formulation of ANM and the release of T. candefacta at the beginning of the growing season of the weed, which allowed to suppress its growth by half.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".