Bibliographic record
Abstract
Botanical insecticides continue to be a subject of keen interest among the international research community, reflected in the steady growth in scientific publications devoted to the subject. Until very recently though, the translation of that theory to practice, i.e. the commercialisation and adoption of new botanical insecticides in the marketplace, has seriously lagged behind. Strict regulatory regimes, long the bane of small pesticide producers, are beginning to relax some of the data requirements for 'low-risk' pesticide products, facilitating movement of more botanicals into the commercial arena. In this paper I discuss some of the jurisdictions where botanicals are increasingly finding favour, some of the newer botanical insecticides in the plant and animal health arsenal and some of the specific sectors where botanicals are most likely to compete effectively with other types of insecticidal product.
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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".