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Record W7017588482

Barite, Anhydrite and Gypsum Reference Materials forIn SituOxygen and Sulfur Isotope Ratio Measurements

2024· article· en· W7017588482 on OpenAlexaboutno aff

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2024
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsnot available
Fundersnot available
KeywordsGypsumReproducibilityIsotopeAnalytical Chemistry (journal)Mass spectrometrySulfurAnhydriteIsotope-ratio mass spectrometry
DOInot available

Abstract

fetched live from OpenAlex

Secondary ion mass spectrometry was used to test the d18O and d34S nanogram-scale homogeneity of a suite of candidate sulfate minerals, ultimately selecting three barite, two anhydrite, and two gypsum samples from the Royal Ontario Museum that have repeatabilities for their SIMS measurements of better than 0.39‰ and 0.37‰ (1s) for oxygen and sulfur isotope ratios, respectively. Metrological splits of each of the seven materials were sent to multiple gas source isotope ratio mass spectrometry laboratories in order to establish their absolute 18O/16O and 34S/32S ratios. The inter-laboratory results of GS-IRMS analyses yielded reasonably narrow ranges in d18OVSMOW, whereas larger variations in d34SVCDT values were found between the results from the gas source laboratories. All samples have good reproducibility within laboratories of GS-IRMS 103d18O values of between 0.24‰ and 0.44‰ (1s). The reproducibility within laboratories of GS-IRMS 103d34S values range from 0.07‰ to 0.99‰ (1s). Here we also discuss some of the current analytical limitations affecting these isotope-mineral systems. A total of 256 metrological splits have been prepared from each of these seven materials; these aliquots will be made available to the global geochemical community.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.082
GPT teacher head0.351
Teacher spread0.269 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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