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Record W4416199298 · doi:10.1111/jfb.70269

Monthly differences in the movement ecology of lake whitefish ( <scp> <i>Coregonus clupeaformis</i> </scp> ) in eastern Lake Ontario

2025· article· en· W4416199298 on OpenAlexafffundabout
Benjamin L. Hlina, Emma J. Bloomfield, Brent W. Metcalfe, Timothy B. Johnson

Bibliographic record

VenueJournal of Fish Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of WindsorMinistry of Natural Resources and Forestry
FundersMinistry of Natural Resources
KeywordsHabitatShoreHydrobiologyLimnetic zoneLimnologyStratification (seeds)Ridge

Abstract

fetched live from OpenAlex

Lake whitefish are a cold-water species that holds cultural and economic importance throughout the Great Lakes region. Anthropogenic stressors over the last 60 years (e.g., invasive species, habitat degradation, and pollution) have caused significant declines in their populations. Furthermore, there is limited knowledge on the spatial ecology and habitat use of the species in Lake Ontario. Therefore, we used acoustic telemetry to quantify horizontal and vertical habitat use by lake whitefish over a 3-year period (2021-2024) in Lake Ontario. We also evaluated seasonal changes in bottom-oriented versus suspended behaviours. Lake whitefish were heavily concentrated along the central Duck-Galloo Ridge and in 20-30 m during periods of stratification (June to September), while their distribution shifted to the south shore of Prince Edward County and 10-25 m during isothermal conditions (non-stratified; October to May) and for spawning. During the isothermal period, lake whitefish exhibited a predominantly bottom-oriented behaviour; during stratification, they exhibited both suspended and bottom-oriented behaviours. These differences in vertical and horizontal distribution may be driven by changes in thermal habitats and/or prey; however, further exploration is needed. Ongoing ecological change may influence lake whitefish distribution and behaviours, necessitating changes to monitoring and/or management that accounts for observed behaviours.

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 score0.793
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.214
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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