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DIET OF HARP SEALS (<i>PAGOPHILUS GROENLANDICUS</i>) IN NEARSHORE NORTHEAST NEWFOUNDLAND: INFERENCES FROM STABLE‐CARBON (δ<sup>13</sup>C) AND NITROGEN (δ<sup>15</sup>N) ISOTOPE ANALYSES

2000· article· en· W1987174725 on OpenAlexaffabout
John W. Lawson, Keith A. Hobson

Bibliographic record

VenueMarine Mammal Science · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTrophic levelGadusClupeaPredationCapelinδ15NBiologyIsotope analysisFisheryδ13CHerringIsotopes of nitrogenStable isotope ratioEcologyEnvironmental scienceFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Trophic position, and often the source of feeding of predators in food webs, can be estimated using measurements of stable isotope ratios of nitrogen and carbon in predators and their prey. Muscle samples from 60 harp seals (Pagophilus groenlandicus) collected during May 1995 in nearshore waters of New foundland, Canada, were analyzed for δ13C and δ15N values. These values were compared with those for 63 prey samples representing seven species generally collected near the same area. Using diet‐tissue isotopic fractionation factors derived from previous studies using captive animals, we infer a greater dependence of harp seals on lower trophic‐level prey during April compared with results expected from exclusive diets of Atlantic cod (Gadus morhua), Atlantic herring (Clupea harengus), Greenland halibut (Reinhardtius hippoglossoides), or northern shrimp (Pandalus borealis). Our mean δ15N value for harp seals is lower than previous findings for seals collected on the winter whelping patch and may be a function of interannual or seasonal differences in diet. Subadult seals (aged 1‐4 yr) had significantly lower δ15N values than adults (5 + yr), suggesting that older seals were feeding at a slightly higher trophic level.

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 score0.790
Threshold uncertainty score0.418

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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

Citations49
Published2000
Admission routes2
Has abstractyes

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