Bibliographic record
Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2000FX ARMA filtersAuthors: Mauricio D. SacchiHenning KuehlMauricio D. SacchiUniversity of Alberta and Henning KuehlUniversity of Albertahttps://doi.org/10.1190/1.1815858 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1815858FiguresReferencesRelatedDetailsCited ByIncreasing the Lateral Resolution of 3D-GPR Datasets through 2D-FFT Interpolation with Application to a Case Study of the Roman Villa of Horta da Torre (Fronteira, Portugal)20 August 2022 | Remote Sensing, Vol. 14, No. 16Accelerated Signal-and-Noise OrthogonalizationIEEE Transactions on Geoscience and Remote Sensing, Vol. 60Acoustic impedance estimation from combined harmonic reconstruction and interval velocityLuca Bianchin, Emanuele Forte, and Michele Pipan29 March 2019 | GEOPHYSICS, Vol. 84, No. 3Signal leakage in f-x deconvolution algorithmsNecati Gülünay25 August 2017 | GEOPHYSICS, Vol. 82, No. 5Amplitude preservation in multicomponent processing using local similarityKhemraj Shukla* and Priyank Jaiswal19 August 2015Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularizationYangkang Chen, Sergey Fomel, and Jingwei Hu5 August 2014 | GEOPHYSICS, Vol. 79, No. 5FX plus deconvolution for seismic data noise reductionMike Galbraith and Zhengsheng Yao25 October 2012Multicomponent f-x seismic random noise attenuation via vector autoregressive operatorsMostafa Naghizadeh and Mauricio Sacchi24 February 2012 | GEOPHYSICS, Vol. 77, No. 2f-x adaptive seismic-trace interpolationMostafa Naghizadeh and Mauricio D. Sacchi12 December 2008 | GEOPHYSICS, Vol. 74, No. 1Adaptive F‐X interpolation of curved seismic events via exponentially weighted recursive least squares (EWRLS)Mostafa Naghizadeh and Mauricio D. Sacchi15 December 2008 SEG Technical Program Expanded Abstracts 2000ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2000 Pages: 2484 publication data© 2000 Copyright © 2000 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 04 Jan 2005 CITATION INFORMATION Mauricio D. Sacchi and Henning Kuehl, (2000), "FX ARMA filters," SEG Technical Program Expanded Abstracts : 2092-2095. https://doi.org/10.1190/1.1815858 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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.181 | 0.120 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".