Physiological effects of capturing Kemp's ridley sea turtles, <i>Lepidochelys kempii</i>, in entanglement nets
Bibliographic record
Abstract
Blood samples were collected from 58 wild Kemp's ridley sea turtles (Lepidochelys kempii) to examine the physiological effects of capture in entanglement nets. Captured turtles were placed in holding tanks or in-water cages to examine whether the postcapture holding protocol influenced the time course of recovery of blood homeostasis. Lactate concentrations at capture were 4.5 ± 0.3 and 3.5 ± 0.3 mmol/L (mean ± SE) for L. kempii assigned to the in-water-cage and holding-tank treatments, respectively. Turtles held in holding tanks for 1 h exhibited a significant increase in lactate concentration over capture levels, whereas lactate concentrations in the cage-held animals did not change. Lactate concentrations declined to less than 1.0 mmol/L by 6 and 10 h post capture for turtles in the in-water-cage and holding-tank treatments, respectively. Plasma norepinephrine (NE) and epinephrine (E) concentrations at capture were substantially elevated above base-line levels reported in the literature for comparably sized loggerhead sea turtles (Caretta caretta). Turtles in holding tanks exhibited greater reductions in NE and E at 1 h post capture than did their counterparts in the in-water cages. Although plasma Na+ and Cl- concentrations were not affected by entanglement netting, K+ concentration was elevated in tank-held L. kempii at 1 h post capture. Taken together, these data indicate that entanglement netting causes significant physiological disturbance in sea turtles and that recovery of blood homeostasis is influenced by the postcapture holding protocol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".