Rare, Threatened and Endangered Zoology Species of Oregon (2025)
Bibliographic record
Abstract
This publication provides a 2025 update to the rare, threatened, and endangered zoology species of Oregon. Species lists are also provided in Excel format. The Oregon Biodiversity Information Center (ORBIC) is part of the Institute for Natural Resources (INR) located at Portland State University (PSU). ORBIC maintains extensive databases of Oregon biodiversity, concentrating on rare and endangered plants, animals and ecosystems. Since its creation in 1979 as the Oregon Natural Heritage Program, ORBIC has been part of the Natural Heritage network. ORBIC is a constituent member of NatureServe, a non-profit organization with a mission to provide the scientific basis for effective conservation action. NatureServe and Oregon manage data using standards and protocols used across the U.S., Canada, and much of Latin America. ORBIC has a primary mission to track the distribution and status of all of Oregon’s flora and fauna, including all vertebrates and vascular plants, and as many invertebrates, fungi, and lichens as is possible. For species considered to be at-risk in Oregon or across the planet, location and population data is managed for all of the observations and occurrences in the state. These data, and the knowledge of the many professional and amateur biologists across the state, provide the basis of the status information in this list.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 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 teacher head, 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".