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Record W3181649473 · doi:10.1071/mf21051

Individual variation influences avoidance behaviour of invasive common carp (Cyprinus carpio) and native buffalo (Ictiobus) to stroboscopic and acoustic deterrents

2021· article· en· W3181649473 on OpenAlexafffund
Paul A. Bzonek, Jaewoo Kim, Nicholas E. Mandrak

Bibliographic record

VenueMarine and Freshwater Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersFisheries and Oceans Canada
KeywordsCommon carpCyprinusBiologyAvoidance behaviourAvoidance responseSound pressureBioacousticsFisheryAudiologyEcologyAcousticsFish <Actinopterygii>Psychology

Abstract

fetched live from OpenAlex

Uncontrolled biological invasions are reducing freshwater ecosystem diversity and resilience. Research is needed to evaluate whether non-structural deterrents are feasible within lock or canal environments. This study examined common carp (Cyprinus carpio) and buffalo hybrid (Ictiobus) movement patterns in response to acoustic and stroboscopic deterrents. Twelve strobe lights and one underwater speaker were deployed across the centre of a ship slip, with an environment analogous to a navigation canal. Common carp (n = 6) and Ictiobus (n = 4) were implanted with acoustic telemetry tags, and their behaviours were examined under control, stroboscopic, and acoustic stimuli for 60-min trial periods. Trials were run during the day and night for six straight days. Linear models determined that the stroboscopic and acoustic stimuli altered fish positioning within the ship slip, but produced weaker avoidance responses than those observed elsewhere. Weak responses were likely due to a strong preference for the open end of the ship slip and a lack of acoustic refuge during the acoustic treatment. Avoidance responses also differed widely among individuals of the same species, with fish expressing repeatability of avoidance radius size across trials. Ambient and stimulus sound-pressure levels should be carefully considered when deploying acoustic deterrents.

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 score0.137
Threshold uncertainty score0.874

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.038
GPT teacher head0.303
Teacher spread0.265 · 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

Citations12
Published2021
Admission routes2
Has abstractyes

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