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Record W2267336516 · doi:10.1371/journal.pone.0148617

Implantation and Recovery of Long-Term Archival Transceivers in a Migratory Shark with High Site Fidelity

2016· article· en· W2267336516 on OpenAlexaboutno aff
Danielle E. Haulsee, Dewayne A. Fox, Matthew W. Breece, Tonya M. Clauss, Matthew J. Oliver

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationUniversity of Delaware
KeywordsCarchariasNova scotiaTransceiverFisheryTerm (time)TelemetryFidelityFish <Actinopterygii>EcologyGeographyEnvironmental scienceBiologyOceanographyArchaeologyGeologyTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

We developed a long-term tagging method that can be used to understand species assemblages and social groupings associated with large marine fishes such as the Sand Tiger shark Carcharias taurus. We deployed internally implanted archival VEMCO Mobile Transceivers (VMTs; VEMCO Ltd. Nova Scotia, Canada) in 20 adult Sand Tigers, of which two tags were successfully recovered (10%). The recovered VMTs recorded 29,646 and 44,210 detections of telemetered animals respectively. To our knowledge, this is the first study to demonstrate a method for long-term (~ 1 year) archival acoustic transceiver tag implantation, retention, and recovery in a highly migratory marine fish. Results show low presumed mortality (n = 1, 5%), high VMT retention, and that non-lethal recovery after almost a year at liberty can be achieved for archival acoustic transceivers. This method can be applied to study the social interactions and behavioral ecology of large marine fishes.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
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 head0.012
GPT teacher head0.191
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 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

Citations19
Published2016
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicIchthyology and Marine BiologyFrench-language works237,207