Visualization of drifting buoy deployments on St. Clair River near public water intakes - October 3-5, 2000
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
St. Clair River is a connecting channel of the Great Lakes between Lake Huron and Lake St. Clair. The river forms part of the international boundary between the United States and Canada in the eastern Lower Peninsula of Michigan and southern Ontario. Drifting buoys were deployed to help investigate flow characteristics near public water intakes in ten reaches of St. Clair River from October 3-5, 2000. In eight deployments, buoys were released at uniform intervals in a transect across the river to better understand flow patterns. In the remaining six deployments, buoys were released in a cluster near the middle of the channel to study turbulent dispersion characteristics. The eight spherical and seven cylindrical buoys used in the study were equipped with drogues and had similar drift characteristics. Each buoy contained a geographical positioning system (GPS) to monitor its movement. Computer animations were developed that integrated these GPS data with data shown on navigational charts. These computer animations, which can be viewed through the Internet, provide a scientific visualization tool to study the deployments.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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