Bibliographic record
Abstract
With continuous threats facing our freshwater systems, scientists and fisheries managers require methods to evaluate the health of freshwater fishes.Previously, many health metrics were evaluated using tissue samples lethally taken from fish.However, with technological advances many of the same parameters can be evaluated with only small pieces of tissue taken from a living specimen.Such non-lethal biopsies have been evaluated in laboratory settings to ensure survival after biopsy, however their impact on fine-scale behaviour, fitness, and stress has yet to be evaluated.In this thesis, three separate studies were conducted on male Smallmouth Bass, juvenile Lake Trout, and adult male Walleye to evaluate the consequences of biopsy procedures.Parental care behaviour in Smallmouth Bass (attack scores generated in response to simulated predation, return to nest time) were similar among biopsy methods, however multiple biopsy types (taken from the same fish) was a strong predictor in nest abandonment.Juvenile Lake Trout exploratory behaviour and response to a novel object was not found to be impacted by biopsy treatments, nor was their performance in an exhaustive exercise test.Finally, reflexes and gene expression (Glucocorticoid Receptor 1, Major Histocompatibility Complex Class 2) were not found to differ in adult male Walleye.Collectively, this body of work suggests that biopsy can be conducted on live teleost fish with negligible impacts on welfare or fitness.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".