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Record W4390532710 · doi:10.1130/g51689.1

Mechanisms of nitrogen isotope fractionation at an ancient black smoker in the 2.7 Ga Abitibi greenstone belt, Canada

2024· article· en· W4390532710 on OpenAlexaboutno aff
A. Martin, Eva E. Stüeken, Julie Michaud, Carsten Münker, Stefan Weyer, Edmond H.P. van Hees, Michelle M. Gehringer

Bibliographic record

VenueGeology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftNatural Environment Research CouncilSight Research UKLeverhulme Trust
KeywordsGreenstone beltGeologyGeochemistryFractionationIsotopeArcheanChemistry

Abstract

fetched live from OpenAlex

Abstract The biological nitrogen (N) cycle on early Earth is enigmatic because of limited data from Archean (meta-)sediments and the potential alteration of primary biotic signatures. Here we further investigate unusual 15N enrichments reported in 2.7 Ga meta-sediments from the Abitibi greenstone belt, Canada, purportedly related to a 15N-enriched Archean atmosphere. Given that sediments from this region are contemporaneous with large-scale volcanogenic massive sulfide deposits, we utilize Cu and Zn contents to trace the effects of hydrothermal circulation on N isotope fractionation. We show that high δ15Nbulk values as high as +23‰ are associated with Cu-Zn mineralization, whereas unmineralized organic-rich shales exhibit much lower δ15Nbulk and δ15Nkerogen values. Moreover, we find a large offset between δ15Nbulk and δ15Nkerogen of as much as 17‰ and relate this to the addition of organic-bound N during the late-stage emplacement of organic-rich veins. We conclude that the previously reported high δ15N values are most parsimoniously explained by biotic and abiotic mechanisms rather than a 15N-enriched atmosphere. Crucially, both mechanisms require the presence of NH4+ in hydrothermal fluids, supporting the hypothesis that hydrothermal discharge was an important nutrient source for Neoarchean marine life.

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)0.001
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 score0.487
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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
Published2024
Admission routes1
Has abstractyes

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