Investigation into the ecological costs of sea lamprey control on lake sturgeon and ammocoete predators using olfactory techniques
Bibliographic record
Abstract
Fish that feed or travel in low light conditions particularly rely on their chemical \nsenses, such as olfaction, for survival. Exposure to toxicants at concentrations lower \nthan those causing mortality can have detrimental effects on olfactory senses. \nMy research studied sea lamprey control from two ecological perspectives. The first was to determine if \nthe lampricide 3-trifluoromethyl-4-nitrophenol (TFM) affects the olfactory \ncapabilities and behaviour of young-of-the-year (YOY) lake sturgeon (Acipenser fulvescens), reduces food consumption and induces a change in blood glucose and lactate. \nMy methods utilized electro-olfactography (EOG), behavioural trials and \nblood analysis. The second part of my study investigated the attraction of lake sturgeon to the \nscent of lamprey ammocoetes as a food source, using chemosensory baits in four northwestern Ontario locations. Laboratory exposure of YOY lake sturgeon to TFM \ncaused a reduced olfactory response to L-alanine, taurocholic acid and a food cue. It also reduced attraction to the scent of food and food consumption in the same species. \nExposed fish were active for a higher percentage of time, but with slower acceleration. \nFish were able to detect the scent of TFM, but did not significantly avoid it, which may \nexpose fish to the full toxic effects. A number of small aquatic predators were attracted \nto ammocoete-conditioned baits. Healthy populations of these species may benefit sea \nlamprey control and help to restore ecological processes that would improve the \nfunctional performance of the Laurentian Great Lakes ecosystem.
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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 | 0.000 |
| 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".