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Record W2162349666 · doi:10.1139/f06-048

Transgenerational marking of embryonic otoliths in marine fishes using barium stable isotopes

2006· article· en· W2162349666 on OpenAlexvenueno aff
Simon R. Thorrold, Geoffrey P. Jones, Serge Planes, Jonathan A. Hare

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersAustralian Research CouncilOak FoundationNational Science Foundation
KeywordsBiologyPelagic zoneBenthic zonePopulationBiological dispersalLarvaZoologyOtolithFisheryHatcheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We describe a new technique for transgenerational marking of embryonic otoliths that promises significant advancements in the study of larval dispersal and population connectivity in marine fishes. The approach is based on maternal transmission of 137Ba from spawning females to egg material that is ultimately incorporated into the otoliths of embryos produced by an individual after exposure to the isotope. We injected females of a benthic-spawning clownfish (Amphiprion melanopus) and a pelagic-spawning serranid (Centropristis striata) with enriched 137BaCl2 and then reared the resulting progeny through to settlement. Barium isotope ratios in the cores of larval otoliths were quantified using laser ablation inductively coupled plasma mass spectrometry. Larval otoliths from both species contained unequivocal Ba isotope signatures over a wide range of doses (0.8–23 µg 137Ba·g female–1). Female A. melanopus continued to produce marked larvae over multiple clutches and for at least 90 days after a single injection. The ability to administer different combinations of stable Ba isotopes provides a new means of mass-marking larvae of benthic- and pelagic-spawning fishes from multiple populations over extended spawning periods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.228
Teacher spread0.205 · 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

Citations143
Published2006
Admission routes1
Has abstractyes

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