Bibliographic record
Abstract
Since its inception as a model system, Caenorhabditis elegans has provided insight about the mechanism of action of drugs through genetic analyses. With the arrival of diverse drug-like small molecule libraries sometime later, the worm also became a platform for drug discovery that was previously inaccessible to academics. Here, the history of larger-scale drug screens using C. elegans is reviewed. The current approaches used to identify the targets and targeted pathways of the novel hits from these screens are also discussed. We focus on the development of small molecule tools for biological investigation, the discovery of novel candidate nematicides and anthelmintics, and touch on screens related to other areas of biology, including neurodegeneration. Finally, we draw attention to the fundamental aspects of C. elegans biology that lends itself to chemical genetic research. When combined with diverse small molecule libraries, the worm's tractability and genetic power make it an unparalleled whole-animal model system for early-stage drug discovery.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".