Estimating incision healing rate for surgically implanted acoustic transmitters from recaptured fish
Bibliographic record
Abstract
Intracoelomic implantation of electronic tags has become a common method in fishery research, but rarely are fish examined by scientists after release to understand the extent that surgical incisions have healed. Walleye ( Sander vitreus ) are a valuable, highly exploited fishery resource in the Laurentian Great Lakes. Here, fishery capture of walleye with internal acoustic transmitters combined with a high reward program provided multiple opportunities to examine photographs and quantify the status of surgical incisions. Walleye ( n = 926) from reef and river spawning populations in Lake Erie and Lake Huron were implanted with acoustic transmitters during spring spawning events from 2011 to 2016. Incisions were closed with polydioxanone monofilament using two to three interrupted sutures. Out of 276 recaptured fish, 60 incision sites were clearly visible in photographs, and these were scored by two independent readers for incision closure, inflammation, and the presence of sutures. While incision sites were completely closed by 61 days post-release (95% CI 44–94), sutures remained for up to 866 days. Sutures were expelled serially during a protracted period, and the probability of observing at least one suture in a recaptured fish declined below 50% after 673 days (95% CI 442–1016). Inflammation at the incision increased during the first 71 days and then declined monotonically, remaining detectable at low levels. Our results emphasized that sutures remained in free-ranging fish past the time when they were beneficial for incision healing. Most dissolvable sutures have been designed for use in endotherms where the body temperature and internal milieu differ dramatically from the conditions experienced by fishes in temperate climates. Identification of new suture materials for fish that facilitate healing while absorbing or dissolving in a reasonable period (e.g., a few weeks to three months) in colder temperatures (e.g., <12 °C) would be beneficial to mitigate potential adverse impacts from inflammation at the incision.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".