MétaCan
Menu
Back to cohort
Record W2038071859 · doi:10.1190/1.1817803

Resonance scattering analysis of 3‐component VSP data

2003· article· en· W2038071859 on OpenAlexaffabout
B. Milkereit, Thomas Bohlen, Wei Qian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComponent (thermodynamics)GeologyResonance (particle physics)ScatteringComponent analysisComputer scienceSeismologyPhysicsOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2003Resonance scattering analysis of 3‐component VSP dataAuthors: Bernd MilkereitThomas BohlenWei QianBernd MilkereitUniversity of Toronto, Dept. of Physics, Toronto, Canada M5S 2J8, Thomas BohlenKiel University, Geosciences, 24118 Kiel, Germany, and Wei QianUniversity of Toronto, Dept. of Physics, Toronto, Canada M5S 2J8https://doi.org/10.1190/1.1817803 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1817803FiguresReferencesRelatedDetailsCited By8. Vertical Seismic Profiles through Gas-Hydrate-Bearing SedimentsIngo A. Pecher, Bernd Milkereit, Akio Sakai, Mrinal K. Sen, Nathan L. Bangs, and Jun-Wei Huang21 March 2012 SEG Technical Program Expanded Abstracts 2003ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2003 Pages: 2452 publication data© 2003 Copyright © 2003 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 03 Jan 2005 CITATION INFORMATION Bernd Milkereit, Thomas Bohlen, and Wei Qian, (2003), "Resonance scattering analysis of 3‐component VSP data," SEG Technical Program Expanded Abstracts : 2274-2277. https://doi.org/10.1190/1.1817803 Plain-Language Summary PDF DownloadLoading ...

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.303

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)0.0000.000

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 head0.025
GPT teacher head0.295
Teacher spread0.270 · 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 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

Citations2
Published2003
Admission routes2
Has abstractyes

Explore more

Same topicElectron Spin Resonance StudiesFrench-language works237,207