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Record W2788388631

Acoustic and Strobe-light Behavioural Barriers: Examining Behavioural and Movement Responses of Common Carp (Cyprinus carpio) at Laboratory and Mesocosm Scales

2017· dissertation· en· W2788388631 on OpenAlexfundno aff
Paul A. Bzonek

Bibliographic record

VenueTSpace (University of Toronto) · 2017
Typedissertation
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsMesocosmCyprinusStimulus (psychology)Common carpCarpAudiologyPsychologyBiologyFisheryEcologyFish <Actinopterygii>MedicineCognitive psychology
DOInot available

Abstract

fetched live from OpenAlex

Acoustic and strobe-light behavioral barriers have been recognized as tools to limit the spread of Asian carps in the Great Lakes. Urgent research is needed to understand how these stimuli impact behaviour, and to evaluate barrier efficacy within realistic canal environments. In a laboratory study, Common Carp responses to stimuli were recorded with video trials (n=44). There were no differences in behavioural responses to acoustic, strobe-light, or combined stimuli. The stimulus period increased durations of carp movement, and the post-stimulus period had increases in movement duration and barrier passes. In a mesocosm study, Common Carp (n=6) and buffalo (n=3) were exposed to the same stimuli, and movement was analyzed using acoustic telemetry. Acoustic stimuli did not produce significant movement responses. Strobe lights (n=12) produced smaller utilization distributions, a decrease in relocations, and an increase in travel velocity near the stimuli (

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)→Same topicFish Ecology and Management Studies→French-language works237,207→