The Effects of Biotelemetry Transmitter Presence and Attachment Procedures on Fish Physiology and Behavior
Bibliographic record
Abstract
Biotelemetry—the process of conveying data from a transmitter-attached animal to a data collection site—has received increasing awareness from fisheries researchers. Prior to biotelemetry data collection, it is imperative that researchers are aware of and understand the possible effects that transmitter presence and attachment procedures may have on ‘normal’ fish behavior and physiology. To allow successful transmitter attachment, numerous methods to anesthetize the study fish, with varied impact and effectiveness, may be employed. Following anesthetization, three standard methods of transmitter attachment have been developed—external attachment, intragastric insertion, and surgical implantation. Although each method has advantages and disadvantages, their success largely depends on factors such as the species, environment, fish and transmitter size, and duration of the telemetry study. Additionally, each method of attachment can affect experimental fish physiology and behavior in varying ways. After describing each of the transmitter attachment procedures, we review the effects of transmitter presence and attachment procedure on fish physiology and behavior, with special focus on implications to aquaculture and fisheries related studies.
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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 | 0.001 |
| 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) | 0.002 | 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 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".