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Record W7038769829

Investigation into the ecological costs of sea lamprey control on lake sturgeon and ammocoete predators using olfactory techniques

2016· dissertation· en· W7038769829 on OpenAlexfundaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2016
Typedissertation
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersMinistry of Natural ResourcesNorthwestern University
KeywordsFish <Actinopterygii>EctothermPopulationExclosure
DOInot available

Abstract

fetched live from OpenAlex

Fish that feed or travel in low light conditions particularly rely on their chemical &#13;\nsenses, such as olfaction, for survival. Exposure to toxicants at concentrations lower &#13;\nthan those causing mortality can have detrimental effects on olfactory senses. &#13;\nMy research studied sea lamprey control from two ecological perspectives. The first was to determine if &#13;\nthe lampricide 3-trifluoromethyl-4-nitrophenol (TFM) affects the olfactory &#13;\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.&#13;\nMy methods utilized electro-olfactography (EOG), behavioural trials and &#13;\nblood analysis. The second part of my study investigated the attraction of lake sturgeon to the &#13;\nscent of lamprey ammocoetes as a food source, using chemosensory baits in four northwestern Ontario locations. Laboratory exposure of YOY lake sturgeon to TFM &#13;\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. &#13;\nExposed fish were active for a higher percentage of time, but with slower acceleration. &#13;\nFish were able to detect the scent of TFM, but did not significantly avoid it, which may &#13;\nexpose fish to the full toxic effects. A number of small aquatic predators were attracted &#13;\nto ammocoete-conditioned baits. Healthy populations of these species may benefit sea &#13;\nlamprey control and help to restore ecological processes that would improve the &#13;\nfunctional performance of the Laurentian Great Lakes ecosystem.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.231
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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