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Record W4416015205 · doi:10.1002/9781394229185.ch8

The Effect of Seawater <scp>Sr</scp> Concentration on the Hydrothermal Alteration of Oceanic Crust: <scp>Sr</scp> Isotopes in Dikes of the Early Paleozoic Bay of Islands Ophiolite

2025· other· en· W4416015205 on OpenAlexaff
Daniel A. Stolper, Daniel Ibarra, Amanda L. Bednarick, Claire E. Bucholz, L. A. Coogan, K. M. Gillis, Max K. Lloyd, John N. Christensen, Donald J. DePaolo

Bibliographic record

VenueGeophysical monograph · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSeawaterOceanic crustOphioliteDikeBasaltHydrothermal circulationBayPaleozoicCrust

Abstract

fetched live from OpenAlex

Oceanic crust is composed of basaltic rocks that have been hydrothermally altered at mid-ocean ridges by circulating heated seawater. Alteration changes the 87 Sr/ 86 Sr of oceanic crust, especially in sheeted dike sections, because seawater has high 87 Sr/ 86 Sr and sufficient dissolved Sr to affect the rocks. The inference that paleoseawater Sr concentrations have been higher than in the modern ocean suggests that ancient examples of altered oceanic crust should record evidence of elevated seawater Sr concentrations, a possibility supported by comparison of Cretaceous ophiolites and Neogene oceanic crust. To further evaluate this relationship, we measured Sr isotopes in sheeted dikes and other oceanic crustal samples of the 488 Ma Bay of Islands (BOI) ophiolite, which formed when seawater may have had the highest Sr concentration of any time during the Phanerozoic, 7 times higher than modern oceans and ∼2.5 times higher than mid-Cretaceous oceans. Our results are consistent with the inferred high Ordovician seawater Sr concentrations. The Sr isotope effects in the BOI ophiolite are not much larger than those in the Cretaceous ophiolites, but the BOI rock Sr concentrations are unusually high, suggesting that a high seawater Sr concentration is needed to account for the Sr isotope effects.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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