Comparison of Detection Efficiency among Three Sizes of Half-Duplex Passive Integrated Transponders Using Manual Tracking and Fixed Antenna Arrays
Bibliographic record
Abstract
Abstract We compared detection efficiency for three lengths (12, 23 and 32 mm) of half-duplex (HDX) passive integrated transponder (PIT) tags for both manual tracking and fixed array applications. In a stream we used a wand-type manual tracking antenna and determined that detection efficiency was considerably influenced by tag size (i.e., 20% for 12 mm, 43% for 23 mm, and 81% for 32 mm) and water depth. Vertical and horizontal read range also varied among tag sizes (lower for smaller tags) and orientation (12-mm and 23-mm tags oriented perpendicularly failed to read in the horizontal test). Using a fixed PIT array, we also compared the detection efficiency of the same three sizes of PIT tags in Shorthead Redhorse Moxostoma macrolepidotum released into a fishway. Again, detection efficiency increased with tag size: 12 mm = 55.8 ± 9.2% (mean ± SE), 23 mm = 91.0 ± 1.8%, and 32 mm = 97.0 ± 1.5%. When using PIT telemetry on smaller fish species and/or life stages, we suggest that researchers consider the tag size, as the diminished detection efficiency of 12-mm tags could introduce a bias and impede the ability to address some research questions. Received July 11, 2012; accepted September 20, 2012
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".