Does 2D:4D predict fitness in a wild mammal?
Bibliographic record
Abstract
Environmental pressures present during critical periods in fetal development can have a strong influence on the long-term fitness of an individual. Susceptibility to parasites, immune function, and future reproductive success are all vulnerable to stressful events in utero. The causes and consequences of prenatal environmental stress are often difficult (if not impossible) to evaluate, especially in wild populations. Digit ratio, the ratio of 2nd digit to 4th digit length (2D:4D) has been identified as an index of fetal androgen exposure. Current techniques for assessing digit ratio pose severe limitations to the accuracy of digit measurement of wild animals owing to the constant movement of the feet and inaccessibility of laboratory equipment. Our study attempts a new indirect technique wherein subjects had an imprint taken of each foot that was then photographed and scanned for digital measurement. Using red squirrels ( Tamiasciurus hudsonicus (Erxleben, 1777)) as a model species, we hypothesized that higher degrees of fetal testosterone exposure (assumed from digit ratios) would result in reduced reproductive success and increased susceptibility to parasite infection. Digit ratio was negatively correlated with reproductive output and positively correlated with parasite loads. Although this may indicate that exposure to excess testosterone in utero may jeopardize future fitness, the relationships are inconsistent.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".