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Record W2366255264 · doi:10.1002/2015gl066479

Poroelastic response of mid‐ocean ridge hydrothermal systems to ocean tidal loading: Implications for shallow permeability structure

2016· article· en· W2366255264 on OpenAlexfundno aff
Thibaut Barreyre, Robert A Sohn

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersUniversity of VictoriaWoods Hole Oceanographic Institution
KeywordsHydrothermal ventHydrothermal circulationGeologyPoromechanicsPermeability (electromagnetism)RidgeOceanographyMid-ocean ridgeAmplitudeSeabedPetrologyGeophysicsSeismologyPaleontologyGeotechnical engineeringPorous mediumPorosity

Abstract

fetched live from OpenAlex

Abstract We use the time delay between tidal loading and exit‐fluid temperature response for hydrothermal vents to model the poroelastic behavior and shallow upflow zone (SUZ) effective permeability structure of three mid‐ocean ridge (MOR) sites with different spreading rates. Hydrothermal vents at Lucky Strike field exhibit relatively small phase lags corresponding to high SUZ effective permeabilities of ≥ ~10 −10 m 2 , with variations that we interpret as resulting from differences in the extrusive layer thickness. By contrast, vents at East Pacific Rise site exhibit relatively large phase lags corresponding to low SUZ effective permeabilities of ≤ ~10 −13 m 2 . Vents at Main Endeavour field exhibit both high and low phase lags, suggestive of a transitional behavior. Our results demonstrate that tidal forcing perturbs hydrothermal flow across the global MOR system, even in places where the tidal amplitude is very low, and that the flow response can be used to constrain variations in SUZ permeability structure beneath individual vent fields.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.282
Teacher spread0.256 · 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 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

Citations27
Published2016
Admission routes1
Has abstractyes

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