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Record W2328787596 · doi:10.1190/segam2014-0344.1

Far-field superresolution by imaging of resonance scattering

2014· article· en· W2328787596 on OpenAlexaff
Gerard T. Schuster, Yunsong Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsKootenay Association for Science & Technology
FundersKing Abdullah University of Science and Technology
KeywordsSuperresolutionScatteringField (mathematics)Resonance (particle physics)OpticsPhysicsComputer scienceArtificial intelligenceImage (mathematics)Atomic physicsMathematics

Abstract

fetched live from OpenAlex

Summary We show that superresolution imaging in the far-field region of the sources and receivers is theoretically possible if migration of resonant multiples is employed. A resonant multiple is one that bounces back and forth between two scattering points or two neighboring reflectors. For a source with frequency ƒ, N roundtrips in propagating between two scatterers increases the effective frequency to 2N × f and decreases the effective wavelength λ to λ/2N. Thus, interbed multiples can, in principle, be used as high-frequency probes to estimate detailed properties of layers. This is not only applicable to crustal reflections, but also to mantle and core reverberations of interest to earthquake seismologists.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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