Brown trout movement data in Glen and Grand Canyons, Arizona, USA
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
These data were compiled to test hypotheses regarding drivers of movement of brown trout. Objectives of our study were to test whether the degree of movement varied in response to placement of a weir in Bright Angel Creek, fall timed flooding events, or simply seasonal changes. These data represent summarized capture histories of brown trout in terms of states based on physical locations, data on removal efforts in Bright Angel Creek, and summaries of effort in the mainstem Colorado River. These data were collected at several locations along the Colorado River in Glen and Grand Canyon, including Bright Angel Creek from 2011 to 2018. These data were collected by U.S. Geological Survey, National Park Service, and Arizona Game and Fish. These data can be used to test hypotheses regarding drivers of brown trout movement in the Colorado River in its Grand Canyon segment.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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