Bibliographic record
Abstract
The spatial distributions of several small mammals in Nunavik, Québec, Canada, currently do not rely on any recorded observations due to the rarity of wildlife surveys in that area. This is concerning because understanding changes in wildlife populations in response to the rapidly warming Arctic requires knowledge of prior population states. On 18 July 2021, my assistant and I captured a least weasel ( Mustela nivalis Linnaeus, 1766) alive, 11 km southwest of Salluit during a live-trapping session of lemmings and voles. Identification was done with the small body mass (44 g), the presence of prominent testicles indicating maturity, short length of the tail, and pale colour at the tip of the tail. All these criteria combined fit only the description of least weasels. According to the available records for this species, this observation is the first one confirmed in Nunavik. This Low Arctic area was already included in the species distribution described in the literature, but no record supported it up to now. It is of particular importance considering this species is susceptible to be designated as threatened or vulnerable in the province of Quebec according to the Centre de données sur le patrimoine naturel du Québec.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".