A Snow-tracking Protocol Used to Delineate Local Lynx, <em>Lynx canadensis</em>, Distributions
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
Determining Canada Lynx (Lynx canadensis) distribution is an important management need, especially at the southern extent of the species range where it is listed as threatened under the U. S. Endangered Species Act. We describe a systematic snowtrack based sampling framework that provides reliable distribution data for Canada Lynx. We used computer simulations to evaluate protocol efficacy. Based on these simulations, the probability of detecting lynx tracks during a single visit (8 km transect) to a survey unit ranged from approximately 0.23 for surveys conducted only one day after snowfall, to 0.78 for surveys conducted 7 days after a snowfall. If the survey effort was increased to three visits, then detection probabilities increased substantially from 0.58 for one day after snowfall to about 0.95 for surveys conducted 7 days after a snowfall. We tested the protocol in the Garnet Range, Montana, where most lynx were radio-collared. We documented a total of 189 lynx tracks during two winters (2001-2003). Lynx distribution based on snow-track surveys was coincident with the area defined through radio telemetry. Additionally, we conducted snow-track surveys in areas of western Wyoming where lynx were believed present but scarce. We detected a total of six lynx tracks during three winters (1999-2002). In Wyoming , where lynx presence was inferred from a few tracks, we verified species identification by securing genetic samples (hairs from daybeds) along track-lines.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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