Nanoization of Technical Pesticides: Facile and Smart Pesticide Nanocapsules Directly Encapsulated through “On Site” Metal–Polyphenol Coordination Assembly for Improved Efficacy and Biosafety
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
Facile pesticide nanocapsules were successfully prepared by directly encapsulating the antisolvent precipitation of pesticides through instantaneous “on site” coordination assembly of tannic acid and Fe 3+, avoiding tedious preparation, time consumption, and large amounts of organic solvents. The pesticide nanocapsules showed excellent resistance to ultraviolet photolysis and rainwater washing owing to the nanocapsule walls. The smart pesticide nanocapsules exhibited the controlled release of pesticides under multidimensional stimuli, such as acidic/alkaline pH, glutathione, H 2 O 2, phytic acid, laccase, tannase, and sunlight, which were related to the physiological and natural environments of crops, pests, and pathogens. The tebuconazole nanocapsules not only enhanced the fungicidal activity against Fusarium graminearum and effective control efficacy in wheat powdery mildew through foliar spray and seed coating, but also improved the biosafety of target plant growth and nontarget organisms. The facile, smart, efficient, safe, and green pesticide nanocapsules using the universal strategy have broad application prospects in ecoagriculture.
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) | 0.000 | 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 | 0.000 |
| 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 it