Game Camera Footage of Beaver-Impacted Streams on the Baldwin Peninsula, Alaska, August 2023-April 2024
Bibliographic record
Abstract
### Access Data files can be accessed and downloaded from the directory via: [https://arcticdata.io/data/10.18739/A2M03Z00G](https://arcticdata.io/data/10.18739/A2M03Z00G) ### Overview Emergence of beavers as ecosystem engineers in the New Arctic project focuses on establishing field sites at tundra beaver ponds to study the implications of beaver engineering on ecosystems. We established three game camera sites at beaver-impacted streams on the Baldwin Peninsula from August 2023-April 2024. We aimed to collect information regarding ice formation phenology, overflow dynamics, and wildlife interactions. Two cameras were deployed adjacent to beaver dams, and another was deployed at a "control" site in a part of a stream that remains unimpacted by beavers. Cameras were set in a hybrid setting, collecting images through timelapse and trigger settings. Two cameras (Moultrie brand) lost power in early December, and one (Bushnell brand) maintained power over the entire study period. Cameras captured ice formation dynamics in early fall, as well as a series of overflow events. From this rudimentary data set, we did not detect differences in ice formation between ponds and the control site. We were also able to detect a dam bursting event following an August rain storm, which beavers did not repair before winter. Cameras captured a variety of wildlife, including red foxes, moose, brown bears, Canada geese, green-winged teal, and, of course, beavers.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.169 |
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; both teacher heads agree on what is shown here.
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".