White monkey syndrome and presumptive copper deficiency in wild savannah baboons
Bibliographic record
Abstract
In immature wild savannah baboons (Papio cynocephalus), we observed symptoms consistent with copper (Cu) deficiency and, more specifically, with a disorder referred to as white monkey syndrome (WMS) in laboratory primates. The objectives of this study were to characterize this pathology, and test three hypotheses that (1) Cu deficiency may have been induced by zinc (Zn) toxicity, (2) it may have been induced by molybdenum (Mo) toxicity, and (3) cumulative rainfall during the perinatal period and particularly during gestation is an ecological factor distinguishing infants afflicted with WMS from non-WMS infants. During 2001-2009, we observed 22 instances of WMS out of a total 377 live births in the study population. Visible symptoms exhibited by WMS infants included whitening of the animal's fur and/or impaired mobility characterized by an apparent "stiffening" of the hindlimbs. Occurrence of WMS did not vary significantly by gender. However, among individuals that survived at least 180 days, WMS males had a significantly lower survivorship probability than non-WMS males. Zn/Cu ratios assessed from hair samples of adult female baboons were higher in females who had produced at least one WMS offspring relative to females who had not had a WMS offspring. This was true even when the hair sample was collected long after the birth of the female's afflicted infant. We consider this potentially indicative of a robust tendency for low Cu levels induced by elevated Zn intake in some individuals. No significant differences of Mo/Cu ratios were observed. Cumulative rainfall during gestation (∼179 days) was 50% lower for WMS infants relative to non-WMS infants. In contrast, rainfall for the two classes of infants did not differ in the 180 days before conception or in the 180 days following birth. This finding highlights the importance of prenatal ecological conditions in healthy fetal development with regard to WMS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".