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Record W3120739985 · doi:10.7755/fb.118.4.8

Seasonal distribution and habitat use of the common thresher shark (Alopias vulpinus) in the western North Atlantic Ocean inferred from fishery-dependent data

2020· article· en· W3120739985 on OpenAlexaffabout
Jeff Kneebone, Heather D. Bowlby, Joseph J. Mello, Camilla T. McCandless, Lisa J. Natanson, Brian J. Gervelis, Gregory B. Skomal, Nancy E. Kohler, Diego Bernal

Bibliographic record

VenueFishery Bulletin · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersSoutheast Fisheries Science CenterNational Oceanic and Atmospheric Administration
KeywordsFisheryHabitatGeographyOceanographyBiologyEcologyGeology

Abstract

fetched live from OpenAlex

Improved understanding of the seasonal distribution, habitat use, and fishery interactions of the common thresher shark (Alopias vulpinus) in the western North Atlantic Ocean (WNA) is required for future management. We compiled and analyzed 3478 fisherydependent capture records in the WNA between 1964 and 2019 to examine dynamics by sex and life stage (i.e., young of the year, juvenile, and adult). Sharks were captured over a broad geographic range from the Gulf of Mexico to the Grand Banks, primarily in continental shelf waters shallower than 200 m. Seasonal north-south movements along the east coasts of the United States and Canada were observed for all life stages and both sexes, with individuals generally occurring at more northerly latitudes in the summer and more southerly latitudes in the winter. Distinct areas of more frequent capture in fisheries were identified for all life stages throughout their range. Common thresher sharks were observed in waters with sea-surface temperatures of 4-31C, most commonly of 12-18C. The results of this study will help to identify essential fish habitat for each life stage of common thresher sharks along the U.S east coast and to develop management measures for the WNA population.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

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 science0.0010.001
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 head0.033
GPT teacher head0.220
Teacher spread0.187 · 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.

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

Citations10
Published2020
Admission routes2
Has abstractyes

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