Best Practices for Evaluation of Bone Marrow in Nonclinical Toxicity Studies
Bibliographic record
Abstract
This manuscript is intended to provide a best practice approach to accurately and consistently assess toxicant-induced bone marrow effects of test articles. In nonclinical toxicity studies, complete blood count data in conjunction with the histological examination of the bone marrow are recommended as the foundation for assessing the effect of test articles on the hematopoietic system. This approach alone can be used successfully in many studies. However, in some situations it may be necessary to further characterize effects on the different hematopoietic lineages, either by cytological or flow cytometric evaluation of the bone marrow. Both modalities can be used successfully, and which one is selected will depend on the expertise, preference of the facility, and the nature of the change in the bone marrow. Other specialized techniques such as clonogenic assays or electron microscopy are used rarely to further characterize hematotoxicity. The indications and techniques to successfully employ histological, cytological, or flow cytometric evaluation as well as clonogenic assays and electron microscopy are reviewed.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".