MétaCan
Menu
Back to cohort
Record W2049721893 · doi:10.1139/f09-196

Turnover and fractionation of carbon and nitrogen stable isotopes in tissues of a migratory coastal predator, summer flounder (Paralichthys dentatus)

2010· article· en· W2049721893 on OpenAlexvenueno aff
Andre Buchheister, Robert J. Latour

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsFlounderFractionationParalichthysStable isotope ratioBiologyIsotope analysisOlive flounderAnimal scienceTurnoverJuvenileIsotopes of nitrogenChemistryEcologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Migratory and mobile fishes such as summer flounder ( Paralichthys dentatus ) often utilize dietary resources with stable isotope signatures that vary over time and space, potentially confounding diet analyses if tissues with slow turnover are sampled before reaching isotopic equilibrium. A laboratory diet-shift study was conducted using juvenile and young adult summer flounder to (i) determine isotopic turnover rates and fractionations of δ13C and δ15N in liver, whole blood, and white muscle and (ii) estimate the relative importance of growth and metabolic processes on isotopic turnover. Isotopic turnover rates were consistently ranked liver > blood > muscle owing to increased metabolic activities of liver and blood. Carbon and nitrogen half-lives ranged from 10 to 20 days (liver), 22 to 44 days (blood), and 49 to 107 days (muscle), indicating that liver and blood are more useful than muscle as shorter-term dietary indicators for summer flounder and other migratory fishes. Growth-based fractionation estimates of wild flounder tissues ranged from 0.71‰ to 3.27‰ for carbon and from 2.28‰ to 2.80‰ for nitrogen and included the first explicit estimates for isotopic fractionation in fish blood. A generalized model for predicting the time scale of isotopic turnover from growth-based turnover parameters was also developed to help evaluate isotopic equilibrium assumptions of fishes in the field.

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 score0.014
Threshold uncertainty score0.029

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 studies0.0000.000
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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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

Citations284
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207