MétaCan
Menu
← Back to cohort
Record W3049260201

Riverine evidence for isotopic mass balance in the Earth's early sulfur cycle

2018· article· en· W3049260201 on OpenAlexaboutno aff
Mark A. Torres, Guillaume Paris, Jess F. Adkins, Woodward W. Fischer

Bibliographic record

VenueAGU Fall Meeting Abstracts · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsArcheanGeologySedimentary rockEarth scienceCrustMass-independent fractionationIsotopeSulfurGeochemistryIsotope fractionationChemistry
DOInot available

Abstract

fetched live from OpenAlex

During a time of negligible atmospheric pO_2, Earth’s early sulfur cycle generated a spectacular geological signal seen as the anomalous fractionation of multiple sulfur isotopic ratios. The disappearance of this signal from the geologic record has been hypothesized to constrain the timing of atmospheric oxygenation, although interpretive challenges exist. Asymmetry in existing S isotopic data, for example, suggests that the Archaean crust was not mass balanced, with the implication that the loss of S isotope anomalies from the geologic record might lag the rise of atmospheric O_2. Here, we present new S isotopic analyses of modern surface and groundwaters that drain Archaean terrains in order to independently evaluate Archaean S cycle mass balance. Natural waters contain sulfur derived from the underlying bedrock and thus can be used to ascertain its S isotopic composition at scales larger than typical geological samples allow. Analyses of 52 water samples from Canada and South Africa suggest that the Archaean crust was mass balanced with an average multiple S isotopic composition equivalent to the bulk Earth. Overall, our work supports the hypothesis that the disappearance of multiple S isotope anomalies from the sedimentary record provides a robust proxy for the timing of the first rise in atmospheric O_2.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.269
Teacher spread0.248 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueAGU Fall Meeting Abstracts→Same topicIsotope Analysis in Ecology→French-language works237,207→