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Record W4323049064 · doi:10.1038/s41598-023-30222-w

Comparison between strip sampling and laser ablation methods to infer seasonal movements from intra-tooth strontium isotopes profiles in migratory caribou

2023· article· en· W4323049064 on OpenAlexaff
Maël Le Corre, Vaughan Grimes, Rebecca Lam, Kate Britton

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsMemorial University of Newfoundland
FundersLeverhulme TrustAlaska Department of Fish and GameMax-Planck-GesellschaftMassachusetts Department of Fish and Game
KeywordsEnamel paintTooth enamelIsotopes of strontiumStrontiumInductively coupled plasma mass spectrometryMineralogyEnvironmental scienceIsotope analysisIsotopeChemistryGeologyEnvironmental chemistryMass spectrometryMaterials scienceOceanographyPhysicsChromatography

Abstract

fetched live from OpenAlex

Abstract Strontium isotopes analysis is a powerful tool in the study of past animal movements, notably the sequential analysis of tooth enamel to reconstruct individual movements in a time-series. Compared to traditional solution analysis, high resolution sampling using laser-ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) has the potential to reflect fine scale mobility. However, the averaging of the 87 Sr/ 86 Sr intake during the enamel mineralization process may limit fine scale inferences. We compared solution and LA-MC-ICP-MS 87 Sr/ 86 Sr intra-tooth profiles from the second and third molars of 5 caribou from the Western Arctic herd, Alaska. Profiles from both methods showed similar trends, reflecting the seasonal migratory movements, but LA-MC-ICP-MS profiles showed a less damped 87 Sr/ 86 Sr signal than solution profiles. Geographic assignments of the profile endmembers to the known summer and winter ranges were consistent between methods and with the expected timing of enamel formation but showed discrepancy at a finer scale. Variations on LA-MC-ICP-MS profiles, consistent with expected seasonal movements, suggested more than an admixture of the endmember values. However, more work in understanding enamel formation in Rangifer , and other ungulates, and how 87 Sr/ 86 Sr daily intake translates into enamel are needed to assess the real resolution that can be achieved with LA-MC-ICP-MS.

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 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 score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.043
GPT teacher head0.312
Teacher spread0.270 · 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.

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

Citations15
Published2023
Admission routes1
Has abstractyes

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