Using Passive Integrated Transponder (PIT) Tags to Investigate Sediment Transport in Gravel-Bed Rivers
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".