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Record W3000874417 · doi:10.1111/ggr.12315

Copper Isotopic Analysis in Geological and Biological Reference Materials by MC‐ICP‐MS

2020· article· en· W3000874417 on OpenAlexaff
Kaj Sullivan, Daniel Layton‐Matthews, Matthew I. Leybourne, J.A. Kidder, Zoltán Mester, Lu Yang

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsNational Research Council CanadaQueen's UniversityGeological Survey of Canada
FundersNational Institute of Standards and Technology
KeywordsHydrosphereSedimentCopperBasaltEnvironmental chemistryBiosphereOil shaleMineralogyGeologyGeochemistryEnvironmental scienceChemistryPaleontologyEcology

Abstract

fetched live from OpenAlex

The characterisation of relative copper isotope amount ratios (δ 65 Cu) helps constrain a variety of geochemical processes occurring in the geosphere, biosphere and hydrosphere. The accurate and precise determination of δ 65 Cu in matrix reference materials is crucial in the effort to validate measurement methods. With the goal of expanding the number and variety of available geological and biological materials, we have characterised the δ 65 Cu values of ten reference materials by MC‐ICP‐MS using C‐SSBIN model for mass bias correction. SGR‐1b (Green River shale), DOLT‐5 (dogfish liver), DORM‐4 (fish protein), TORT‐3 (lobster hepatopancreas), MESS‐4 (marine sediment) and PACS‐3 (marine sediment) have for the first time been characterised for δ 65 Cu. Additionally, four reference materials (with published δ 65 Cu values) have been characterised: BHVO‐1 (Hawaiian basalt), BIR‐1 (Icelandic basalt), W‐2a (diabase) and Seronorm™ Trace Elements Serum L‐1 (human serum). The reference materials measured in this study possess complex and varied matrices with copper mass fractions ranging from 1.2 µg g −1 to 497 µg g −1 and δ 65 Cu values ranging from −0.20‰ to 0.52‰ with a mean expanded uncertainty of ± 0.07‰ ( U , k = 2), covering much of the natural copper isotope variability observed in the environment.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.069
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.088
GPT teacher head0.360
Teacher spread0.272 · 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

Citations51
Published2020
Admission routes1
Has abstractyes

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