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High-precision triple oxygen isotope analysis of Archean and Proterozoic carbonates

2020· article· en· W3087681738 on OpenAlexaff
Oliver Jäger, Jakub Surma, Nina Albrecht, Chris S. Marien, Wanli Xiang, Katharina Schier, Michael Bau, Joachim Reitner, Andreas Pack

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsThermo Fisher Scientific (Canada)
Fundersnot available
KeywordsChemistryArcheanBioinorganic chemistryIsotopeStereochemistryBiologyPhysics

Abstract

fetched live from OpenAlex

Oxygen isotopes are a widely used tracer in the field of paleoceanography and provide unique information on mineral formation and environmental conditions. Carbonate sediments record a shift in δ18O of 10 to 15‰ from the Archean towards higher values in the Phanerozoic. Three different scenarios are suggested to explain this observation: (I) hot Archean oceans, (II) depletion of 18O in Archean oceans compared to present day and (III) diagenetic alteration of the primary isotopic signature [1]. Recent advances in high-resolution gas source isotope ratio mass spectrometry provide a new tool that may allow to decipher the origin of this isotopic shift observed in the early rock record. We performed high-precision 18O/16O and 17O/16O measurements on oxygen ion fragments (16O+, 17O+, 18O+) generated in the ion source from CO2 gas [2]. Isobaric interferences on m/z=17 (16OH+) and m/z=18 (H216O+) are separated by means of high mass resolution. The CO2 gas is first liberated from carbonate samples by orthophosphoric acid digestion and then analyzed on a Thermo Scientific Ultra dual-inlet gas source isotope ratio mass spectrometer [3]. By adding the dimension of 17O/16O to the classical 18O/16O system, equilibrium trajectories of carbonates that are defined by the equilibrium fractionation factor (18aeq) and the triple isotope fractionation exponent (θ) can be predicted as a function of temperature. Minerals that were altered by or formed in meteoric water can be distinguished from those that precipitated in equilibrium with ambient sea water. Therefore, triple oxygen isotope analysis of carbonates does not only hold the potential for a new single-phase paleothermometer, but may also be used to trace the origin of carbonates. Here, we present high-precision triple oxygen isotope data for carbonates from the Pilbara and the Kaapvaal cratons that cover nearly one billion years from the Paleoarchean to the Paleoproterozoic. Marine carbonates from the Phanerozoic complement the dataset. The carbonates were formed in different marine settings, from shallow marine stromatolites to carbonates grown in the interstitial space of basaltic pillows. Phanerozoic carbonates record equilibrium conditions with modern sea water at moderate temperatures. The majority of Precambrian carbonates plot below the predicted equilibrium curve in the δ’18O-Δ‘17O space and do not reflect equilibrium conditions with modern sea water at elevated temperatures that were proposed for the Archean oceans. Modeling the triple oxygen isotope composition of carbonates in equilibrium with sea water, that is depleted in 18O also cannot explain the observed isotopic shift. Further modeling of post-depositional alteration suggests that most carbonates interacted and re-equilibrated with meteoric waters at variable water-rock ratios and temperatures. [1] Shields and Veizer, 2002, Geochem., Geophy., Geosyst., 10.1029/2001GC000266 [2] Getachew et al., 2019, Rapid Commun. Mass. Spectrom., 10.1002/rcm.847 [3] Eiler et al., 2013, Int. J. Mass. Spectrom., 335, 45-56.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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