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Record W1976390086 · doi:10.1577/m08-143.1

The Use of Stable Oxygen Isotope (δ18O) Composition in Sockeye Salmon Body Fluid to Determine whether a Fish Has Been Caught in Freshwater

2009· article· en· W1976390086 on OpenAlexaff
Robie W. Macdonald, V. Forsland, Ruth E. Withler, David A. Patterson, Art Demsky

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser UniversityFisheries and Oceans Canada
Fundersnot available
KeywordsOncorhynchusFisheryIsotopes of oxygenFish <Actinopterygii>Environmental scienceBiologyChemistry

Abstract

fetched live from OpenAlex

Abstract Fisheries enforcement is often tasked with determining whether a seized Pacific salmon Oncorhynchus spp. has been caught legally or illegally, either in freshwater while it was migrating to its natal stream or in the ocean at some point during its life cycle or migration. Here we show that the oxygen stable isotope composition (δ18O) of the water within seized fish tissue, together with DNA analysis, provides a powerful means of establishing where the fish was migrating and whether it was inhabiting freshwater when harvested. These tools are relatively easy to apply and are supported by an extensive set of microsatellite DNA data for sockeye salmon O. nerka that provide “forensic” identification and by a time series record for δ18O in the water of the Fraser River. The difference between δ18O composition in the river (∼−17‰) and the ocean (∼−2‰), together with conservative mixing between the end members, provides wide discriminatory power. Evaporation or sublimation during storage favors the light isotope and would thus be to the advantage of the defendant.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 designBench or experimental
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

Citations2
Published2009
Admission routes1
Has abstractyes

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