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Record W4312180132 · doi:10.1111/jfb.15297

Boldness, movement and exploration tendency in round goby (<i>Neogobius melanostomus</i>) in Southern Ontario

2022· article· en· W4312180132 on OpenAlexaffabout
Emily J. Yeung, Sandra Klemet‐N'Guessan, Thomas J. Hossie, Michael G. Fox

Bibliographic record

VenueJournal of Fish Biology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrent UniversityDalhousie University
Fundersnot available
KeywordsRound gobyNeogobiusBoldnessBiologyHabitatEcologyInvasive speciesRange (aeronautics)Front (military)Introduced speciesFisheryZoologyGeographySocial psychologyPersonalityPsychology

Abstract

fetched live from OpenAlex

Invasive species have the potential to damage ecosystems outside their native range. At an invasion front, individuals are faced with the unfamiliar conditions of a novel environment. Therefore, certain behavioural traits such as boldness and movement likely play a role in invasion ecology. If behavioural traits of this kind are influenced by differing selection pressures between demographic groups of the same species, this could have broad implications for the management of expanding invasion fronts. To determine whether the invasive round goby (Neogobius melanostomus, Pallas, 1814) exhibits sex- and habitat-based differences in boldness and movement across the invasion front, the authors assessed individual movement and exploration tendency under controlled lab settings using video analysis in a behavioural assay. N. melanostomus from lakes tended to be bolder than those from streams, and females tended to be bolder than males. This study provides evidence for sex- and habitat-based differences in behaviour in this globally invasive species that the authors hope will assist in forming the foundation for contextually appropriate management strategies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.986

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 studies0.0010.000
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 head0.012
GPT teacher head0.212
Teacher spread0.199 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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