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Record W2155293573 · doi:10.1139/cjfas-2014-0128

Spatiotemporal occurrence of loggerhead turtles (<i>Caretta caretta</i>) on the West Florida Shelf and apparent overlap with a commercial fishery

2014· article· en· W2155293573 on OpenAlexvenueno aff
Robert Hardy, Anton D. Tucker, Allen M. Foley, Barbara A. Schroeder, Robin J. Giove, Anne B. Meylan

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryFishingContext (archaeology)BycatchResidenceGeographyMarine protected areaFisheries managementOceanographyEcologyBiologyHabitatGeology

Abstract

fetched live from OpenAlex

Information on the spatial and temporal distribution of protected marine species is critical for the development of conservation strategies. We examined a 12-year dataset describing the postnesting residence areas of 81 adult female loggerhead turtles (Caretta caretta) on the West Florida Shelf (WFS) in the northeastern Gulf of Mexico. The aggregation of loggerheads on the WFS represents at least four US recovery units for this protected species. We identified several seasonally persistent residence areas that were shared by multiple loggerheads on the WFS. The majority (69%) of individuals remained within a discrete residence area throughout the tracking period. We placed our results within the context of a related fishery management concern — loggerhead bycatch within the bottom longline component of the Gulf commercial reef-fish fishery. We characterized loggerhead residence areas and compared that information with fishing activity. Our results provide information on the distribution of WFS loggerhead residence areas and the extent to which residence areas overlap with areas of high fishing effort. Loggerheads were present year-round on portions of the WFS, within or near to areas with high fishing effort. Interactions among loggerheads and fishing activities could be reduced by conservation management strategies that consider these spatial and seasonal patterns of occurrence.

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)0.001
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 score0.037
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.196
Teacher spread0.179 · 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

Citations25
Published2014
Admission routes1
Has abstractyes

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