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Record W7116086749 · doi:10.1016/j.gca.2025.12.039

Modeling extreme nitrogen isotope variability in Neoarchean diamonds from Knee Lake, Superior Craton

2025· article· en· W7116086749 on OpenAlexafffund

Bibliographic record

VenueGeochimica et Cosmochimica Acta · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsotope fractionationArcheanIsotopeFractionationMantle (geology)Isotopes of carbonCratonIsotopic signature

Abstract

fetched live from OpenAlex

The nitrogen (N) isotope composition of world-wide diamonds shows considerable variability that is uncorrelated with carbon isotopes. Most of this variability is currently explained by different compositions of the N sources, although fractionation processes can nonetheless play a role. Because N in Earth’s mantle is overprinted by subduction as time progresses, we examined the N isotope composition of the Knee Lake diamond suite, hosted in volcaniclastic rocks erupted in the Neoarchean at ∼2.73 Gy, to try to obtain an older glimpse of N isotope variability. Secondary ion mass spectrometry analyses of 186 Knee Lake diamonds revealed extraordinarily varied N isotope compositions, expanding from the lowest (−46.8 ‰) to the highest (+31.8 ‰) values measured for terrestrial diamonds, strongly clustered around a median of −0.7 ‰. The median value indicates a heavier-than modern δ 15 N composition of the Archean mantle, suggesting a secular change from a 15 N-enriched primordial composition. Whether some of the δ 15 N variability in the Knee Lake diamonds could have been inherited by crustal recycled or unmixed primordial sources, the range and discontinuous distribution of the most extreme values rule out an overall explanation as being formed by mixing of heterogeneous N sources and suggests the involvement of fractionation processes. The systematics of N concentration ([N]) and δ 15 N variations for most of the Knee Lake diamonds are permissive of a Rayleigh distillation process. Rayleigh distillation during kinetic isotope fractionation associated with the decomposition of N-phases could even produce the most 15 N-enriched compositions and the uncorrelated [N]-δ 13 C variability. However, Ryleigh fractionation cannot produce the most 15 N-depleted compositions. The extreme N isotope compositions in the Knee Lake diamond suite are correlated with crystal shape, the most negative δ 15 N values occurring in cuboid and the most positive in octahedral crystals. This suggests the operation of kinetic N fractionation processes related to different growth-surface structures or growth conditions. Despite the recognition of distinct N isotope compositions in different growth sectors in synthetic crystals, two mixed-habit Knee Lake diamonds show only a small growth-sector related N isotope variability. The only process we can model that is capable of producing the most 15 N-depleted values is diffusion along chemical gradients, whether pre-existing in the growth environment or generated by crystal growth under diffusion-limited conditions as indicated by the re-entrant, fibrous shape of some cuboid crystals. These observations highlight the complexity of nitrogen isotope geochemistry in the Earth mantle, and suggest that various kinetic effects may play a role in fractionating the N isotope compositions of some diamonds during their growth. The possibility of N isotope fractionation during diamond growth suggests caution in the use of isotopic tracers in presence of extreme values, even at the high temperatures of the Earth mantle.

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 score0.217
Threshold uncertainty score0.432

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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