Bibliographic record
Abstract
The small and mid-sized carnivores (Carnivora), or mesocarnivores of western forests comprise 16 species (coyote ( Canis latrans ), red fox ( Vulpes vulpes ), gray fox ( Urocyon cinereoargenteus ), ringtail ( Bassariscus astutus ), raccoon ( Procyon lotor ), marten ( Martes americana ), fisher ( M. pennanti ), ermine ( Mustela erminea ), long-tailed weasel ( M. frenata ), mink ( M. vison ), wolverine ( Gulo gulo ), northern river otter ( Lontra canadensis ), western spotted skunk ( Spilogale gracilis ), striped skunk ( Mephitis mephitis ), Canadian lynx ( Lynx canadensis ), and bobcat ( Lynx rufus )). The term “forest carnivores” denotes a smaller group of four species – the marten, fisher, lynx, and wolverine – and is only marginally descriptive, inasmuch as it excludes many carnivores that live in forests, and includes the wolverine, which can thrive in the complete absence of trees. The species we consider here represent four (or five (Dragoo and Honeycutt 1997)) taxonomic families and are characterized by adult body weights typically <20 kg. Other mesocarnivores, including the kit fox ( Vulpes macrotis ), swift fox ( V. velox ), least weasel ( Mustela nivalis ), black-footed ferret ( M. nigripes ), and badger ( Taxidea taxus ), occur in the West, occupy habitats near forest edges, and may be conservation concerns. However, they are plains or grassland specialists or, in the case of the least weasel, very poorly known, and cannot be characterized in terms of their needs for forest attributes. So, they are not treated here. Our understanding of the ecology of carnivores in western coniferous forests varies markedly.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".