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Record W4414162981 · doi:10.1139/cjz-2025-0064

Behavioural threshold of adult and juvenile sea lamprey ( <i>Petromyzon marinus</i> ) to acoustic stimuli

2025· article· en· W4414162981 on OpenAlexafffundvenue
Victoria Lynn Smit Heath, Megan F. Mickle, Dennis M. Higgs

Bibliographic record

VenueCanadian Journal of Zoology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of WindsorMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaGreat Lakes Fishery Commission
KeywordsLampreyJuvenilePetromyzonSound (geography)Fish <Actinopterygii>Sound exposure

Abstract

fetched live from OpenAlex

Sea lamprey ( Petromyzon marinus Linnaeus, 1758) are invasive fish species in the Laurentian Great Lakes and parasitically feed on many commercially important fishes. Sound is used as a deterrent for invasive species, but its potential for manipulating sea lamprey behaviour in natural stream conditions is under-tested. Both the behavioural acoustic thresholds and different life stage responses of sea lamprey have yet to be established. To fill in some literature gaps, low-frequency tones of 70 or 90 Hz were used in a laboratory setting to determine the behavioural responses of adult and juvenile sea lamprey. Both stages of sea lamprey exhibited a change in swimming behaviour (movement to the onset and offset of sound) and a twitch (small movement of tail or body) in response to both frequencies. The behavioural threshold for adult and juvenile lamprey to sound ranged from 147 to 162 dB re 1 µPa. The threshold level for twitch determined for 70 Hz for juvenile and adult sea lamprey ranged from 157 to 160 dB re 1 µPa. These thresholds and behaviours can be used for implementation of field management techniques that have previously shown the efficacy of sound to direct lamprey movements for control purposes.

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 score0.006
Threshold uncertainty score0.012

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 integrity0.0000.000
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 head0.009
GPT teacher head0.212
Teacher spread0.204 · 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
Published2025
Admission routes3
Has abstractyes

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