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Record W1982472845 · doi:10.1155/2009/812713

Model-Based Identification of the Base of the Gas Hydrate Stability Zone in Multichannel Reflection Seismic Data, Offshore Costa Rica

2009· article· en· W1982472845 on OpenAlexaff
Romina Gehrmann, Christian Müller, P. Schikowsky, Thomas Henke, Michael Schnabel, Christian Bönnemann

Bibliographic record

VenueInternational Journal of Geophysics · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Victoria
FundersUniversität BremenDeutsche Forschungsgemeinschaft
KeywordsGeologyClathrate hydrateAmplitude versus offsetSubmarine pipelineSeismologyReflection (computer programming)Accretionary wedgeContinental marginAmplitudeTectonicsDeconvolutionHeat flowGeomorphologyMineralogyPetrologyHydrateGeotechnical engineeringThermalOpticsSubductionMeteorology

Abstract

fetched live from OpenAlex

Along the pacific margin offshore Costa Rica the Bottom Simulating Reflector (BSR) shows a patchy occurrence in 2-D seismic reflection profiles. The reason for this can be either lack of free gas beneath parts of the gas hydrate stability zone (GHSZ) or poor seismic imaging. We compare far to near offset stacked common midpoint sections to reduce imaging ambiguity utilizing the amplitude variation with offset effect and thus successfully distinguish BSRs from regular sediment reflections. In combination with 1-D modeling of the base of the GHSZ we disqualify or qualify reflections in the predicted depth range as BSR. Additionally we calculate the heat flow and compare it with an analytical solution to detect thermal anomalies, for example, at the frontal prism. The higher confidence in BSR depths based on the far offset stacks and heat flow calculations allows further analyses on gas hydrate concentration estimates and tectonic evolution of the margin.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.205

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 science0.0010.000
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 head0.270
Teacher spread0.243 · 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 designSimulation or modeling
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

Citations8
Published2009
Admission routes1
Has abstractyes

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