Use of nonhuman primates in research in North America.
Bibliographic record
Abstract
In North America, the biomedical research community faces social and economic challenges to nonhuman primate (NHP) importation that could reduce the number of NHP available for research needs. The effect of such limitations on specific biomedical research topics is unknown. The Association of Primate Veterinarians (APV), with assistance from the Centers for Disease Control and Prevention, developed a survey regarding biomedical research involving NHP in the United States and Canada. The survey sought to determine the number and species of NHP maintained at APV members' facilities, current uses of NHP to identify the types of biomedical research that rely on imported animals, and members' perceived trends in NHP research. Of the 149 members contacted, 33 (22%) replied, representing diverse facility sizes and types. Cynomolgus and rhesus macaques were the most common species housed at responding institutions and comprised the majority of newly acquired and imported NHP. The most common uses for NHP included pharmaceutical research and development and neuroscience, neurology, or neuromuscular disease research. Preclinical safety testing and cancer research projects usually involved imported NHP, whereas research on aging or degenerative disease, reproduction or reproductive disease, and organ or tissue transplantation typically used domestic-bred NHP. The current results improve our understanding of the research uses for imported NHP in North America and may facilitate estimating the potential effect of any future changes in NHP accessibility for research purposes. Ensuring that sufficient NHP are available for critical biomedical research remains a pressing concern for the biomedical research community in North America.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".