Seed Dispersal by Brown Bears, <em>Ursus arctos</em>, in Southeastern Alaska
Bibliographic record
Abstract
Mammals often consume fleshy fruits and disperse significant quantities of the enclosed seeds. In southeastern Alaska, Brown Bears (Ursus arctos) are among the most important dispersers of seeds for the numerous plant species producing fleshy fruits, because these bears are abundant, often eat large quantities of fruit, and commonly excrete seeds in germinable condition. Scat analyses showed that Brown Bears on Chichagof Island ate increasing quantities of fruit through summer and fall. Scats commonly contained several thousand seeds, often of two or more species. Four kinds of seeds of fleshyfruited plants that normally grow in forest understory germinated at similar levels when experimentally deposited (in bear scats) in the two most common habitats (forest and muskeg), suggesting that habitat distribution of these plants is not determined simply by germination patterns. Although seed passage through bear digestive tracts and the composition of scats are known to affect germination rates to some degree, the most important role of bears in seed dispersal is probably transport.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".