Relative use of xeric boreal habitats by shrews (<i>Sorex</i>spp.)
Bibliographic record
Abstract
Abstract Few studies have explicitly examined habitat use by shrews (Sorexspp.) in the boreal forest of western North America. We conducted pitfall trapping in six common xeric habitat types in Yukon, Canada, to determine their relative use by shrews. The overall capture rate was 0.47 shrews per 100 trap nights (TN), with a total sampling effort of 3652 TN. Cinereus shrews (Sorex cinereus; 0.25 per 100 TN) were the most common species, followed by dusky shrews (Sorex monticolus; 0.14 per 100 TN) and American pygmy shrews (Sorex hoyi; 0.08 per 100 TN). Shrew capture rates and species richness was low in all habitat types sampled. Cinereus shrews were captured in similar numbers in boreal mixedwood forest and alpine shrub habitats, and rarely in other lowland forest habitat types. Dusky shrews were captured largely in alpine shrub habitats, while pygmy shrews were captured only in lowland forest habitat types. The relative use of alpine shrub habitat by cinereus shrews and dusky shrews was not expected. Our data was limited by low captures; however, we provide a first approximation of the relative use of common forest types and subalpine shrub habitat in the boreal forest of northwestern Canada.
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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 | 0.001 | 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".