Foreword: Towards markers for anthelmintic resistance in helminths of importance in animal and human health
Bibliographic record
Abstract
Anthelmintic resistance is a serious problem in veterinary medicine and appears to be developing in some helminths of importance to human health. Anthelmintic drugs remain the principal means of control of helminth infections in animals and humans and the continued dependence on these pharmaceuticals will continue to impose selection pressure for resistance development. Our ability to detect anthelmintic resistance before control breaks down and to monitor the spread of anthelmintic resistance is quite limited. We are currently dependent on biological methods which are not sufficiently sensitive to detect low levels of drug resistance and are particularly difficult to perform on helminth parasites of humans. There is a serious need for new molecular markers for detecting and monitoring for anthelmintic resistance. The problem of anthelmintic resistance is already very serious in nematode parasites of livestock. In addition, there should be great concern about possible anthelmintic resistance development and the lack of tools and efforts for monitoring it as part of the major worldwide programmes to control helminth parasites in people. An international Consortium has been formed to develop Anthelmintic Resistance Single nucleotide polymorphism markers (CARS). Discussions within the Consortium have addressed the need for such markers, the current state of knowledge about them, possible mechanisms of anthelmintic resistance and approaches and constraints to the development of markers. Summaries of the state of the art in these areas are presented in a series of papers in this Special Issue of Parasitology.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.050 | 0.056 |
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".