MétaCan
Menu
Back to cohort
Record W2063193742 · doi:10.1039/c0em00347f

Geographic differences in organic contaminants and stable isotopes (δ13C, δ15N) in thick-billed murre (Uria lomvia) eggs from Alaska

2011· article· en· W2063193742 on OpenAlexaff
Stacy S. Vander Pol, Keith A. Hobson, Paul R. Becker, Rusty D. Day, Michael B. Ellisor, Rebecca S. Pugh, David G. Roseneau

Bibliographic record

VenueJournal of Environmental Monitoring · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsEnvironment and Climate Change Canada
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSeabirdIsotopes of nitrogenδ15Nδ13CFood webContaminationStable isotope ratioEnvironmental chemistryIsotope analysisIsotopes of carbonEnvironmental scienceIsotopeEcologyPredationBiologyZoologyTotal organic carbonChemistry

Abstract

fetched live from OpenAlex

The contents from thick-billed murre (Uria lomvia) eggs collected at four Alaskan colonies in 2002 were analyzed for organic contaminants and carbon δ¹³C) and nitrogen (δ¹⁵N) stable isotopes. Contaminant concentrations in the eggs varied from below detection limits to 230 ng g⁻¹ wet mass for 4,4'-DDE in one egg from St Lazaria Island in the Gulf of Alaska. Eggs from this colony generally contained higher levels of contaminants and exhibited significantly different patterns compared to eggs from the Bering and Chukchi seas. Stable isotope values also varied geographically; however, these differences appeared to be related to differences in C and N baselines in the food webs instead of differences in prey. Contaminant and stable isotope correlations were inconclusive, suggesting that better information on regional food web differences and differential offloading of contaminants and stable isotopes to the eggs must be obtained before these kinds of data can be fully incorporated into seabird egg contaminant monitoring programs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.214
Teacher spread0.200 · 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 teacher head, not a consensus.

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

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental MonitoringSame topicIsotope Analysis in EcologyFrench-language works237,207