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Record W4387364508 · doi:10.1130/g51311.1

Seafloor spreading and the delivery of sulfur and metals to Earth’s oceans

2023· article· en· W4387364508 on OpenAlexafffund
Drew D. Syverson, Adedapo N. Awolayo, Benjamin M. Tutolo

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsMcMaster UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsSeafloor spreadingGeologyMid-ocean ridgeSulfideSulfurSeawaterHydrothermal circulationVolcanogenic massive sulfide ore depositGeochemistryMineralogyOceanographyPyriteMantle (geology)ChemistrySphaleriteSeismology

Abstract

fetched live from OpenAlex

Abstract Circulating fluids within Earth’s mid-ocean ridge system cool and alter the oceanic crust, contribute distinct chemistry to the ocean, and generate economically and geologically important metal-sulfide deposits at the seafloor. Yet, we have few constraints on the characteristics of these fluids at peak subseafloor pressure and temperature conditions or how the primary variable, seafloor spreading, affects these fluids’ delivery of metals and sulfur to seawater. Here, we develop a new, robust technique for estimating the peak endowment of heat and dissolved sulfur, iron, and copper in subseafloor hydrothermal fluids and determining their fate as these superheated fluids rise to the seafloor. Calculations using this technique indicate that >20%–70% of sulfur, iron, and copper dissolved at peak subseafloor conditions are lost during upflow due to cooling and concomitant decreases in sulfide mineral solubility. The interpretation of these estimates within the geologic context of vent fields allows us to demonstrate a strong inverse relationship between seafloor spreading rate and peak pressure-temperature conditions, subseafloor heat loss, and the magnitude of subseafloor sulfide mineralization. Our results demonstrate the extent to which the secular variation of Earth’s mid-ocean ridge system over geologic time has impacted sulfide deposition rates and hydrothermal fluxes of sulfur and metals to the ocean.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.184

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 science0.0000.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations16
Published2023
Admission routes2
Has abstractyes

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