Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The extensive and indiscriminate use of chemical pesticides in agriculture has led to adverse effects on human health, environmental pollution, and the emergence of pesticide-resistant pests. To mitigate these challenges, the development of environmentally friendly alternatives is crucial, with biopesticides emerging as promising solutions such as peptides. Legume seeds naturally contain diverse insecticidal peptides or proteins to combat pest attacks. One such peptide is PA1b (Pea Albumin 1, subunit b), a 37 amino acid extracted from pea seeds (<i>Pisum sativum</i>). PA1b has shown significant potential in controlling cereal weevils (<i>Sitophilus</i> spp.), a major pest of stored cereals. Here, we screened PA1b-like peptides in five wild seeds of vetches (<i>Vicia sativa</i> subsp. <i>sativa)</i> from the Middle East. Using a comprehensive set of biochemical, biological, and molecular techniques, we characterized different PA1b homologs and assessed their toxicity and expression profiles. Our results reveal that PA1b homolog from <i>Vicia sativa</i> subsp. <i>sativa</i> originating from turkey displays outstanding insecticidal activity against <i>Sitophilus oryzae</i> through binding to the receptor site found in the midgut of the insect. Moreover, it exhibits a strong cytotoxic effect against Sf9 cells. This cysteine-rich peptide shows sequence identity and the same hydrophobic pole as AG41, a tenfold more toxic isoform of PA1b from <i>Medicago truncatula</i>. Such observations pave the way for the development of bioinsecticides, with PA1b-like peptides as lead compounds.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it