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Record W1976140089 · doi:10.1139/f01-146

Stable isotopic composition of otoliths in identification of spawning stocks of Pacific herring (<i>Clupea pallasi</i>) in Puget Sound

2001· article· en· W1976140089 on OpenAlexvenueno aff
Yongwen Gao, Steve H Joner, Greg G. Bargmann

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPacific herringOtolithSound (geography)ClupeaOceanographyClupeidaeHerringGeologySpawn (biology)AragoniteFisheryFish <Actinopterygii>BiologyMineralogy

Abstract

fetched live from OpenAlex

Otoliths of Pacific herring (Clupea pallasi) were collected from Puget Sound, Washington, and were analysed for oxygen and carbon isotope ratios (δ18O and δ13C). It was expected that if adult herring spawn at different localities with different δ18O and δ13C values, these isotope variations would constitute a natural tag that can be used to distinguish the herring spawning stocks. For a test project, we took aragonite powder samples from the surface of otolith nuclei and the second summer otolith rings, respectively. Isotopic composition of otolith nuclei from the Georgia Strait had lowest isotope values (from –8.2‰ to –2.0‰ VPDB (Vienna Peedee belemnite) in δ18O and –6.8‰ to –3.9‰ VPDB in δ13C), significantly different from those collected from two southern Puget Sound spawning grounds (from –3.9‰ to –0.9‰ VPDB in δ18O and –5.6‰ to –2.0‰ VPDB in δ13C). This isotopic identification is consistent with the biological observation and the actual sample collection. Stable isotopic information extracted from the summer otolith rings, in contrast, showed two types of herring in 1999 corresponding to the migratory and non-migratory stocks in Puget Sound. The rate of the two types of herring was about 70% versus 30%.

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 score0.017
Threshold uncertainty score0.033

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)0.0000.000

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Citations45
Published2001
Admission routes1
Has abstractyes

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