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Record W1601006326 · doi:10.1029/2011gl046870

Release of multiple bubbles from cohesive sediments

2011· article· en· W1601006326 on OpenAlexafffund
Christopher K. Algar, Bernard P. Boudreau, Mark A. Barry

Bibliographic record

VenueGeophysical Research Letters · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchKillam TrustsDalhousie University
KeywordsGeologyMineralogyGeophysics

Abstract

fetched live from OpenAlex

[1] Methane is a strong greenhouse gas, and marine and wetland sediments constitute significant sources to the atmosphere. This flux is dominated by the release of bubbles, and quantitative prediction of this bubble flux has been elusive because of the lack of a mechanistic model. Our previous work has shown that sediments behave as elastic fracturing solids during bubble growth and rise. We now further argue that bubbles can open previously formed, partially annealed, rise tracts (fractures) and that this mechanism can account for the observed preferential release at low tides in marine settings. When this mechanical model is applied to data from Cape Lookout Bight, NC (USA), the results indicate that methanogenic bubbles released at this site do indeed follow previously formed rise tracts and that the calculated release rates are entirely consistent with the rise of multiple bubbles on tidal time scales. Our model forms a basis for making predictions of future bubble fluxes from warming sediments under the influence of climate change.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.045
GPT teacher head0.277
Teacher spread0.232 · 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

Citations40
Published2011
Admission routes2
Has abstractyes

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