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Record W4414061989 · doi:10.3354/meps14978

Horizontal and vertical movements and habitat use of the common thresher shark Alopias vulpinus in the western North Atlantic

2025· article· en· W4414061989 on OpenAlexaboutno aff
Jeff Kneebone, Martin C. Arostegui, Lisa J. Natanson, Gregory B. Skomal, Camrin D. Braun, Diego Bernal

Bibliographic record

VenueMarine Ecology Progress Series · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatJuvenileRange (aeronautics)Continental shelfFish measurementPopulationHome rangeNursery habitat

Abstract

fetched live from OpenAlex

In the western North Atlantic (WNA), the common thresher shark Alopias vulpinus is captured by several fisheries, but its population status has not formally been assessed, and its ecology and population structure are poorly understood. A total of 61 pop-up satellite archival transmitting tags were deployed to study the species’ horizontal and vertical movement patterns and habitat use in the WNA and to inform the formulation of fishery management policy. Tracking data from 48 individuals ranging from 122 to 259 cm fork length revealed widespread horizontal movements throughout the WNA between northeastern Florida north and east to the Grand Banks of Newfoundland. Seasonal migrations across continental shelf and off-shelf habitats were identified in both juveniles and adults. Tagged common thresher sharks inhabited a wide temperature range in the WNA (-0.5 to 25.6°C), but spent ~90% of their time in waters between 14 and 20°C. Depth distribution ranged from the surface to 1822 m, with ~87% of time spent at depths shallower than 50 m. Deeper depths were achieved during the winter, spring, and fall than during the summer. These results will assist with the identification of important geographic locations of occurrence for both juvenile and adult common thresher sharks, help forecast the effects of environmental change on the species’ distribution, and inform the relevant spatial scales for fishery management policies and stock assessment.

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 score0.078
Threshold uncertainty score0.155

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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
Published2025
Admission routes1
Has abstractyes

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