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Record W2908098404 · doi:10.1002/jms.4323

Improved online hydrogen isotope analysis of halite aqueous inclusions

2019· article· en· W2908098404 on OpenAlexaff
François Fourel, Christophe Lécuyer, Magali Seris, Nigel Blamey, Uwe Brand, Philip Fralick, Filip Volders

Bibliographic record

VenueJournal of Mass Spectrometry · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsLakehead UniversityBrock UniversityWestern University
Fundersnot available
KeywordsHaliteChemistryIsotope-ratio mass spectrometryAnalytical Chemistry (journal)Aqueous solutionAnalyserHydrogenMass spectrometryIsotopeFluid inclusionsIsotope analysisMineralogyChromatographyGeology

Abstract

fetched live from OpenAlex

Abstract We demonstrate an improved method based on continuous‐flow elemental analyser pyrolysis isotopic ratio mass spectrometry (CF‐EA‐PY‐IRMS) to measure the 2 H/ 1 H ratios of water trapped in halite crystals. Two challenges to overcome are the low hydrogen concentration of samples (10‐50 μmol H 2 ·g −1 ) and the high chloride concentration released when reacting halite in an elemental analyser. We describe an optimization procedure for determining the 2 H/ 1 H ratio of this trapped water with an acceptable accuracy. This technique involves the use of a high‐temperature Cr reactor to quantitatively convert H 2 O into H 2 . The initial step was performed on halite crystals precipitated from a water reservoir where 2 H/ 1 H ratios were monitored from its initial stage until the end of evaporation. The 2 H/ 1 H isotopic analyses were automated online in continuous‐flow mode. Precision of the method was determined for those “synthetic” samples with hydrogen concentrations ranging from 0.2 to 0.5 wt%. 2 H/ 1 H isotopic ratios of evaporating waters bracket the compositions of water inclusions. The formation of fluid inclusions is not instantaneous and records the isotopic signature of the residual waters across a time range during which the isotopic values of the water still evolve. This property explains why the δ 2 H VSMOW standard deviation of ±5‰ (2σ) observed for 10‐mg aliquots of halite exceeds the instrumental error (about ±1.5‰ 2σ) determined on the basis of IAEA‐CH7, NBS 30, and NBS 22 references along with calibrated waters with and without added halite crystals. We also applied this method to Mesoproterozoic (1.4 Ga) and Neoproterozoic (0.8 Ga) halite samples with relatively low hydrogen concentrations (300‐1500 ppm). The measured δ 2 H VSMOW values for Precambrian waters range from −89‰ to −54‰. We propose that this technique offers a new perspective and great potential for palaeoenvironmental reconstructions based on the 2 H/ 1 H analyses of water trapped in halite.

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)0.000
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 score0.110
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

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