Evaluation of four surgical implantation techniques for age‐0 white sturgeon ( <i>Acipenser transmontanus</i> Richardson, 1836) with a new acoustic transmitter
Bibliographic record
Abstract
The goal of this study was to evaluate four implantation techniques by assessing transmitter retention, survival, growth, and wound healing responses in white sturgeon (Acipenser transmontanus Richardson, 1836). A new acoustic transmitter (AT; cylindrical, 0.7 g in air, 24.2 × 5.0 mm, up to 365 days battery life) was developed to monitor age-0 sturgeon; however, an implantation technique is critical to provide guidance for its use in field research. Sturgeon (n = 150, 182–289 mm fork length, 35–116 g) were separated into five treatments (n = 30 per treatment): (i) control, (ii) flank incision with one suture, (iii) flank incision without a suture, (iv) offline incision with one suture, and (v) offline incision without a suture. Fish were implanted with a non-functioning AT and observed for 28 days. Transmitter retention was 100% and only fish in the offline incision without a suture treatment had reduced growth (0.15% mm growth per day) compared to controls (0.38%) over the 28 days study. Suturing caused an increase in incision inflammation, ulceration, and water mold infection. Offline incisions were more susceptible to varicosities than flank incisions. Non-sutured incisions showed greater incision openness, but only during the first 14 days post-implantation. A flank incision without a suture is recommended for implanting this new AT in age-0 white sturgeon.
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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) | 0.001 | 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) | 0.001 | 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".