Insecticide resistance management and industry: the origins and evolution of the <scp>I</scp>nsecticide <scp>R</scp>esistance <scp>A</scp>ction <scp>C</scp>ommittee (<scp>IRAC</scp>) and the mode of action classification scheme
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
Insecticide resistance is a long-standing problem affecting the efficacy and utility of crop protection compounds. Insecticide resistance also impacts the ability and willingness of companies around the world to invest in new crop protection compounds and traits. The Insecticide Resistance Action Committee (IRAC) was formed in 1984 to provide a coordinated response by the crop protection industry to the problem of insecticide resistance. Since its inception, participation in IRAC has grown from a few agrochemical companies in Europe and the US to a much larger group of companies with global representation and an active presence (IRAC Country Groups) involving an even wider array of companies in more than 20 countries. The focus of IRAC has also evolved from that of defining and documenting cases of insecticide resistance to a pro-active role in addressing insecticide resistance management (IRM) providing an array of informational and educational tools (videos, posters, pamphlets) on insect pests, bioassay methods, insecticide mode of action and resistance management, all publicly available through its website (https://irac-online.org/). A key tool developed by IRAC is the Insecticide Mode of Action (MoA) Classification Scheme, which has evolved from a relatively simple acaricide classification started in 1998 to the far broader scheme that now includes biologics as well as insecticides and acaricides. A separate MoA Classification Scheme has also been recently developed for nematicides. The IRAC MoA Classification Scheme coupled with expanding use of MoA labeling on insecticide and acaricide product labels provides a straightforward means to implement IRM. An overview of the history of IRAC along with some of its notable accomplishments and future directions are reviewed. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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