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Record W2051156910 · doi:10.1130/g21259.1

Bubble growth and rise in soft sediments

2005· article· en· W2051156910 on OpenAlexafffundabout
Bernard P. Boudreau, Christopher K. Algar, Bruce D. Johnson, Ian W. Croudace, Allen Reed, Yoko Furukawa, Kelley M. Dorgan, Peter A. Jumars, A. S. Grader, Bruce S. Gardiner

Bibliographic record

VenueGeology · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchU.S. Naval Research LaboratoryNatural Sciences and Engineering Research Council of CanadaGeological Society of America
KeywordsCoveNova scotiaHistoryLibrary scienceArt historyArchaeologyOceanographyGeologyComputer science

Abstract

fetched live from OpenAlex

The mechanics of uncemented soft sediments during bubble growth are not widely understood and no rheological model has found wide acceptance. We offer definitive evidence on the mode of bubble formation in the form of X-ray computed tomographic images and comparison with theory. Natural and injected bubbles in muddy cohesive sediments are shown to be highly eccentric oblate spheroids (disks) that grow either by fracturing the sediment or by reopening preexisting fractures. In contrast, bubbles in soft sandy sediment tend to be spherical, suggesting that sand acts fluidly or plastically in response to growth stresses. We also present bubble-rise results from gelatin, a mechanically similar but transparent medium, that suggest that initial rise is also accomplished by fracture. Given that muddy sediments are elastic and yield by fracture, it becomes much easier to explain physically related phenomena such as seafloor pockmark formation, animal burrowing, and gas buildup during methane hydrate melting.

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

Distilled classifier scores by category (both heads)

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

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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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

Citations263
Published2005
Admission routes3
Has abstractyes

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