Our Wild Neighbors: Exploring the connection between Portland's people and wildlife
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Urban Wildlife Information Network (UWIN) is a rapidly expanding, international effort to better understand the effect of urban density on wildlife across the U.S. and Canada. Originating eight years ago with the Lincoln Park Zoo in Chicago, IL, today 23 participating cities employ a standardized monitoring protocol that captures wildlife data using trail cameras placed along transects that span a gradient of urban density. Network cities have used the data collected to further research, inform local policy and engage community scientists as well as compare data across municipalities. Portland, Oregon is set to be the next member of the UWIN network. Over the last two years a collaborative effort between Portland State University, Portland Audubon, Samara Group and the Oregon Wildlife Foundation have laid the groundwork to add Portland to the UWIN map. The team has been working to establish camera monitoring transects that extend east and west of downtown Portland. To date 15 cameras have been deployed, documenting roughly 20 species including (coyote, skunk, racoon, and mule deer). The UWIN effort has also engaged PSU students, Audubon interns, and other community members enhancing local knowledge of urban wildlife and monitoring techniques. The team continues to make headway in adding cameras and monitoring locations with the ultimate goal of 30 sites. The UWIN program is a valuable addition to urban wildlife research both locally and internationally.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it