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Record W1599377753 · doi:10.1111/jfb.12660

Regional movement patterns of a small‐bodied shark revealed by stable‐isotope analysis

2015· article· en· W1599377753 on OpenAlexaff
Samantha Munroe, Michelle R. Heupel, Aaron T. Fisk, Murray Logan, Colin A. Simpfendorfer

Bibliographic record

VenueJournal of Fish Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsUniversity of Windsor
FundersJames Cook UniversityGreat Barrier Reef Marine Park AuthorityLinnean Society of NSW
KeywordsBiologyBayChondrichthyesIsotope analysisSeagrassEcologyHabitatTrophic levelElasmobranchiiFisheryZoologyOceanography

Abstract

fetched live from OpenAlex

This study used stable-isotope analysis to define the nearshore regional residency and movements of the small-bodied Australian sharpnose shark Rhizoprionodon taylori. Plasma and muscle δ(13) C and δ(15) N of R. taylori were collected from across five embayments and compared with values of seagrass and plankton from each bay. Linear distances between adjacent bays ranged from 30 to 150 km. There was a positive geographic correlation between R. taylori tissue and environmental δ(13) C values. Populations with the highest tissue δ(15) N were collected from bays that had the highest environmental δ(15) N values. These results suggest that R. taylori did not forage more than 100 km away from their capture location within 6 months to 1 year. The successful application of isotope analysis to define R. taylori movement demonstrates that this technique may be used in addition to traditional methods to study the movement of sharks, even within similar habitats across regionally small spatial scales (<100 km).

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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.024
GPT teacher head0.247
Teacher spread0.222 · 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

Citations18
Published2015
Admission routes1
Has abstractyes

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