Environmental heterogeneity affects seasonal variation in thyroid hormone physiology of free-living arctic ground squirrels (<i>Urocitellus parryii</i>)
Bibliographic record
Abstract
Thyroid hormones (TH) are key regulators of metabolism that could play an important role in altering physiology and energy allocation across life-history stages. Here, we examine seasonal TH dynamics from 345 plasma samples collected from 134 free-living arctic ground squirrels (Urocitellus parryii (Richardson, 1825)) across three consecutive years (2014–2016). We also examine whether unbound levels of triiodothyronine (free T3) in plasma are correlated with total T3 levels and total thyroxine (T4) levels, and whether fecal T3 metabolite levels correlate with plasma TH levels. We found significant differences in plasma TH levels across stages of the annual cycle, but these differences were highly inconsistent across years. However, within a given time period, pregnant females had lower free T3 levels compared with lactating females. We also found that although free T3 was correlated with both total T3 and total T4 in plasma, fecal T3 was not positively correlated with plasma TH levels. Given the lack of consistent differences across life-history stages, we suggest environmental heterogeneity may be the primary driver of TH dynamics, masking any potential endogenous seasonal rhythms in TH secretion. We urge caution in the use of fecal T3 metabolites as a proxy for circulating levels and encourage further research to understand the observed discrepancy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".