Bibliographic record
Abstract
66. Preble’s Shrew Sorex preblei French: Musaraigne de Preble / German: Preble-Spitzmaus / Spanish: Musarana de Preble Other common names: Malheur Shrew Taxonomy. Sorex preblei H. H. T. Jackson, 1922, “ Jordan Valley, altitude 4,200 feet [= 1280 m], Malheur County, Oregon,” USA. Sorex preblei is in the S. cinereus group and subgenus Otisorex. It seems to be sister to a clade including the Beringian clade, S. haydeni, and the south-western lineage in S. cinereus. Monotypic. Distribution. Known from scattered records in the Columbia Plateau and N Great Plains of SC British Columbia (SE Canada), N & SE Washington, Oregon, WC Idaho, Montana, NE California, N Nevada, W Wyoming, and N Utah, although these populations are probably connected and additional collecting efforts are needed. Descriptive notes. Head-body 44-57 mm, tail 28-38 mm, hindfoot 9-11 mm; weight 2-4 g. Preble’s Shrew is very small. Dorsum is grayish brown, with paler sides, and venteris silvery white. Feet are pale buffy, and tail is comparatively short, narrow, and bicolored, being brown above and whitish below. I' has deep interdenticular space. Teeth are pigmented dark red. There are five unicuspids, fifth is the smallest, and third is generally greater than or equal to fourth. Habitat. Primarily arid sagebrush and sagebrush-steppe habitats but also conifer forests, dry bunchgrass habitats, other grassland habitats, and near marshes and wetlands at elevations of 1280-2750 m. Although primarily collected in sagebrush habitats, Preble’s Shrew is probably associated with dry open habitats in general. Food and Feeding. Diet of Preble’s Shrew probably consists of soft-bodied invertebrates. Breeding. Pregnant females and reproductive males have been captured in June-July in Oregon. Litters have 3-6 young (average 4-4). Female Preble’s Shrews probably have multiple litters each year. Activity patterns. No information. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Least Concern on The IUCN Red List. Preble’s Shrew is rarely collected and known from relatively few scattered specimens over a wide distribution, which might be much larger and more connected than what is currently known; collecting efforts using pitfall traps are needed. Fossils are known from the Pleistocene of southern New Mexico. Bibliography. Carraway (1995), Carraway & Verts (1999), Cassola (2016q), Cornely et al. (1992), Demboski & Cook (2003), Gitzen et al. (2009), Hoffmann & Fisher (1978), Hoffmann et al. (1969), Hope et al. (2012), Junge & Hoffmann (1981), Long & Hoffmann (1992), Nagorsen et al. (2001), Ports & George (1990), Tomasi & Hoffmann (1984), Williams (1984).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".