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Low-Temperature Alteration of the Seafloor: Impacts on Ocean Chemistry

2018· article· en· W2792378909 on OpenAlexaff
L. A. Coogan, K. M. Gillis

Bibliographic record

VenueAnnual Review of Earth and Planetary Sciences · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSeafloor spreadingSeawaterGeologyOceanic crustCrustHydrothermal circulationGeophysicsLithosphereBasaltAquiferMid-ocean ridgeSedimentOceanographyMantle (geology)GeochemistryGroundwaterGeomorphologyTectonicsPaleontology

Abstract

fetched live from OpenAlex

Over 50% of Earth is covered by oceanic crust, the uppermost portion of which is a high-permeability layer of basaltic lavas through which seawater continuously circulates. Fluid flow is driven by heat lost from the oceanic lithosphere; the global fluid flux is dependent on plate creation rates and the thickness and distribution of overlying sediment, which acts as a low-permeability layer impeding seawater access to the crust. Fluid-rock reactions in the crust, and global chemical fluxes, depend on the average temperature in the aquifer, the fluid flux, and the composition of seawater. The average temperature in the aquifer depends largely on bottom water temperature and, to a lesser extent, on the average seafloor sediment thickness. Feedbacks between off-axis chemical fluxes and their controls may play an important role in modulating ocean chemistry and planetary climate on long timescales, but more work is needed to quantify these feedbacks.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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
GenreReview

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

Citations131
Published2018
Admission routes1
Has abstractyes

Explore more

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