Minerals in the foods and diet of diademed sifakas: Are they nutritional challenges?
Bibliographic record
Abstract
Minerals, though needed in small quantities, are essential to metabolic processes, and deficiencies can seriously threaten health, reproduction and survival. Despite this, few studies have measured mineral composition of wild primate foods and fewer have quantified mineral intake. Here we measured the concentration of nine minerals in 75 foods of diademed sifakas (Propithecus diadema; five groups) in habitats with varying levels of disturbance at Tsinjoarivo and estimated daily intakes using focal-animal feeding data and intake rates over one year. For six minerals (Ca, P, Na, Fe, Zn, and Cu), mean concentrations in foods fell short of the National Research Council's (NRC) recommendations for captive primates. Concentrations were highest in lianas, herbs, and epiphytes, and hemiparasites had exceptionally high Na. Leaves tended to have higher concentrations than fruits or flowers, but overlap was extensive. Mineral concentrations in daily diets varied little seasonally, but absolute intakes (g/day) were higher in the abundant season, due to the increase in food ingested. Disturbed habitat groups' diets had higher mineral concentrations for five minerals, but this translated into increased intakes only for Cu, as these groups ate less food overall. Overall, comparisons with percentage-based NRC recommendations suggests deficiencies, but this is contradicted by: (1) the fact that mass-specific intakes exceeded human recommendations, and (2) the lack of observed signs of deficiency. Ongoing efforts to quantify mineral consumption across wild primate populations and better understanding requirements on both a percentage and absolute basis will help in understanding effects on food selection, managing primate habitats and formulating captive diets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".