Bacterial populations and metabolites in the feces of free roaming and captive grizzly bears
Bibliographic record
Abstract
Gut physiology, host phylogeny, and diet determine the composition of the intestinal microbiota. Grizzly bears (Ursus arctos horribilis) belong to the Order Carnivora, yet feed on an omnivorous diet. The role of intestinal microflora in grizzly bear digestion has not been investigated. Microbiota and microbial activity were analysed from the feces of wild and captive grizzly bears. Bacterial composition was determined using culture-dependent and culture-independent methods. The feces of wild and captive grizzly bears contained log 9.1 +/- 0.5 and log 9.2 +/- 0.3 gene copies x g(-1), respectively. Facultative anaerobes Enterobacteriaceae and enterococci were dominant in wild bear feces. Among the strict anaerobes, the Bacteroides-Prevotella-Porphyromonas group was most prominent. Enterobacteriaceae were predominant in the feces of captive grizzly bears, at log 8.9 +/- 0.5 gene copies x g(-1). Strict anaerobes of the Bacteroides-Prevotella-Porphyromonas group and the Clostridium coccoides cluster were present at log 6.7 +/- 0.9 and log 6.8 +/- 0.8 gene copies x g(-1), respectively. The presence of lactate and short-chain fatty acids (SCFAs) verified microbial activity. Total SCFA content and composition was affected by diet. SCFA composition in the feces of captive grizzly bears resembled the SCFA composition of prey-consuming wild animals. A consistent data set was obtained that associated fecal microbiota and metabolites with the distinctive gut physiology and diet of grizzly bears.
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 | 0.000 |
| 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 | 0.001 |
| 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".