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Record W2146912561 · doi:10.1139/z05-064

Tracing dietary protein in red-backed voles (<i>Clethrionomys gapperi</i>) using stable isotopes of nitrogen and carbon

2005· article· en· W2146912561 on OpenAlexfundvenueno aff
David T.J Sare, John S. Millar, Fred J. Longstaffe

Bibliographic record

VenueCanadian Journal of Zoology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsotopes of nitrogenNitrogenBiologyStable isotope ratioIsotopeCarbon fibersIsotopes of carbonFractionationAnimal scienceEnvironmental chemistryEcologyChemistryTotal organic carbonChromatography

Abstract

fetched live from OpenAlex

We examined the stable isotopes of nitrogen and carbon in a small mammal, the red-backed vole (Clethroinomys gapperi (Vigors, 1830)), to determine if isotope signatures reflect diet composition. Nitrogen- and carbon-isotope ratios in tissues from voles maintained on different protein levels in the laboratory were compared with wild-trapped voles. The isotopic fractionation of dietary nitrogen and carbon was also examined as food was digested in the stomach, incorporated into bone collagen, bioapatite, and hair, and excreted as feces. Nitrogen and carbon isotopes were fractionated differently depending on the isotopic composition and protein content of the diet. δ15N and δ13C values appear to be influenced by factors in addition to diet, such as macronutrients metabolized for respiration, metabolic rate, and periods of protein shortage.

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 score0.005
Threshold uncertainty score0.010

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 studies0.0000.001
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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Citations54
Published2005
Admission routes2
Has abstractyes

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