Within-sample variability of steroid and thyroid metabolite measurements in faeces of Northeast Pacific resident killer whales (<i>Orcinus orca</i>)
Bibliographic record
Abstract
Abstract Faecal hormone metabolite (FHM) analyses are increasingly used as a non-invasive method to evaluate physiological stress in wild populations, especially those of conservation concern. In cetaceans, faecal collection from the ocean surface results in considerable variation in sample volume and density. Knowledge of the distribution of hormone metabolites within a faecal sample is limited, but is an important consideration when interpreting values. Here we investigated the variability of glucocorticoid (fGCM) and thyroid (fTHM) metabolites within fish-eating resident killer whale faeces by comparing mean concentration, standard deviation (SD) and coefficient of variation (CV) among three treatment groups: sub-samples, pooled sub-samples and homogenized pooled sub-samples from the same defecation event. No significant difference was found in the mean concentration of fGCM and fTHM across treatment groups. The mean SD for fGCM was significantly higher in sub-samples than in pooled and homogenized treatment groups (P &lt; 0.05), while differences in the mean SD of fTHM were not significant among treatment groups. Overall, the CV of FHM measurements was reduced to less than 15% and 10%, respectively, by pooling and homogenizing the sub-samples prior to analysis. We found high correlation in fGCM and fTHM across all treatments, suggesting that values from sub-samples were generally representative of the overall faecal sample. These findings help guide methods for processing cetacean faecal samples and interpreting associated FHM data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".