Using Passive Integrated Transponder (PIT) Tags to Investigate Sediment Transport in Gravel-Bed Rivers
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
Abstract In gravel-bed rivers, measuring the displacement of individual grains by fluid flow is essential in order to understand sediment transport processes and to investigate changes in channel morphology. We present preliminary results of a new technique that traces pebble movements by inserting 23 mm passive integrated transponders (PIT) into individual clasts. Because each PIT has its own signal identification, this technique is ideal for tracking the individual movements of episodically transported particles in gravel-bed rivers. Two hundred and four tagged particles were inserted into a 130-m-long reach of a gravel-bed river with a 2% slope and a bed material with a D50 of 70 mm. The b axis size of the tagged particles ranged from 40 mm to 250 mm. Recovery percentages after two competent floods were 96% and 87%, clearly demonstrating the effectiveness of this new technique. Buried particles can be recovered at a depth of 0.25 m. PIT tags are also suited for long-term studies over several years.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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