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Record W2030120794 · doi:10.1190/1.2792958

3D azimuthal imaging

2007· article· en· W2030120794 on OpenAlexaff
Charles Sicking, Stewart Nelan, William McLain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicOptical measurement and interference techniques
Canadian institutionsGeoscience BC
Fundersnot available
KeywordsAzimuthComputer scienceGeologyRemote sensingComputer graphics (images)OpticsPhysics

Abstract

fetched live from OpenAlex

Azimuthal variations in velocity are observed in many geographic locations. Tectonic stress and depositional patterns are two possible causes for azimuthally dependent velocity fields. In locations where there are variations in the wave propagation velocity as a function of azimuth angle, proper imaging of the subsurface cannot be achieved without the incorporation of azimuthal velocity variation in the imaging algorithm. A Kirchhoff solution to pre‐stack imaging in the presence of azimuthal variations in velocity has been derived. The solution properly accounts for the travel time variation as a function of azimuth in the imaging algorithm. This paper compares isotropic prestack imaging to azimuthal pre‐stack imaging. Correcting for the azimuthal variations on the gathers input to imaging and using isotropic imaging leads to a spatially smeared result. The correctly focused image can be obtained only by accounting for the azimuthal varying travel times in the imaging algorithm.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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 designBench or experimental
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

Citations22
Published2007
Admission routes1
Has abstractyes

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