Evaluation of a method to determine the breeding activity of lemmings in their winter nests
Bibliographic record
Abstract
Winter breeding under the snow is a critical ecological adaptation of lemmings and a key demographic process in their periodic multiannual fluctuations in abundance. However, logistic constraints limit our ability to quantify lemming winter reproduction. We evaluated a method to infer lemming reproduction based on the size distribution of feces found in their winter nests. We determined criteria allowing identification of reproduction from feces found in nests, using golden Syrian hamsters (Mesocricetus auratus) as a surrogate model. We found a large difference in individual mass of feces between juveniles at weaning and adults. Using bimodal distribution of feces size, mean size difference, and proportion of small feces, we showed that visual inspection of ≥30 feces was sufficient to infer hamster reproduction with an accuracy of >95%. We also applied the method to winter nests of collared lemmings (Dicrostonyx groenlandicus) and brown lemmings (Lemmus trimucronatus) found in the Canadian Arctic. Because characteristics of feces found in lemming winter nests matched those found in hamster nests, we suggest that the method can be used to detect winter reproductive activity of lemmings.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".