Challenges and opportunities for the adoption of molecular diagnostics for anthelmintic resistance
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
Anthelmintic resistance is a significant threat to livestock production systems worldwide and is emerging as an important issue in companion animal parasite management. It is also an emerging concern for the control of human soil-transmitted helminths and filaria. An important aspect of managing anthelmintic resistance is the ability to utilise diagnostic tests to detect its emergence at an early stage. In host-parasite systems where resistance is already widespread, diagnostics have a potentially important role in determining those drugs that remain the most effective. The development of molecular diagnostics for anthelmintic resistance is one focus of the Consortium for Anthelmintic Resistance and Susceptibility (CARS) group. The present paper reflects discussions of this issue that occurred at the most recent meeting of the group in Wisconsin, USA, in July 2019. We compare molecular resistance diagnostics with in vivo and in vitro phenotypic methods, and highlight the advantages and disadvantages of each. We assess whether our knowledge on the identity of molecular markers for resistance towards the different drug classes is sufficient to provide some expectation that molecular tests for field use may be available in the short-to-medium term. We describe some practical aspects of such tests and how our current capabilities compare to the requirements of an 'ideal' test. Finally, we describe examples of drug class/parasite species interactions that provide the best opportunity for commercial use of molecular tests in the near future. We argue that while such prototype tests may not satisfy the requirements of an 'ideal' test, their potential to provide significant advances over currently-used phenotypic methods warrants their development as field diagnostics.
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 | 0.001 |
| 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