Intracoelomic Implantation of Transmitters in Longnose Gar
Bibliographic record
Abstract
Abstract Fish in the family Lepisosteidae (hereafter, gars) have unique ganoid scales that pose inherent challenges to implanting electronic tags in their coeloms for telemetry studies. In this paper we outline a unique approach to conducting laparotomic surgery in gars, with a focus on the Longnose Gar Lepisosteus osseus. An electric rotary tool with a circular cutting blade was used to cut through the scales, and the same tool, with a drill bit, was used to create holes through which to run the suture material. The final incision into the body cavity was made with a scalpel, and the incision was expanded using surgical scissors. Using a passive acoustic telemetry array, the survival of 12 of 15 tagged Longnose Gars was confirmed over a 123‐d period based on their detection at receivers outside of their areas of capture and release. Two individuals were recaptured 17–19 weeks postsurgery and showed complete healing of the wounds with limited evidence of scarring. This approach will allow for the long‐term tagging and tracking of gars to help elucidate their ecology.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".