Bibliographic record
Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2000Wide‐angle AVOAuthors: Graham RobertsGraham RobertsVeritasDGC Ltd.https://doi.org/10.1190/1.1815648 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1815648FiguresReferencesRelatedDetailsCited ByWavelet estimation and nonstretching NMO correctionHanlin Sheng, Xinming Wu, and Bo Zhang29 March 2022 | GEOPHYSICS, Vol. 87, No. 3Wavelet estimation and nonstretching NMO correctionHanlin Sheng, Xinming Wu, and Bo Zhang30 September 2020Nonstretch normal moveout through iterative partial correction and deconvolutionEttore Biondi, Eusebio Stucchi, and Alfredo Mazzotti4 June 2014 | GEOPHYSICS, Vol. 79, No. 4Prediction of Shale Plugs between Wells in Heavy Oil Sands using Seismic Attributes8 December 2006 | Natural Resources Research, Vol. 15, No. 2Quantitative Seismic Interpretation27 January 2010 | , Vol. 80Examination of wide‐angle, multi‐component, AVO attributes for prediction of shale in heavy oil sands: A case study from the Long Lake Project, Alberta, CanadaDavid Gray, Paul Anderson, and Jay Gunderson3 January 2005Plane waves, spherical waves and angle‐dependent P‐wave reflectivity in elastic VTI‐modelsArnim B. Haase3 January 2005 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 Graham Roberts, (2000), "Wide‐angle AVO," SEG Technical Program Expanded Abstracts : 134-137. https://doi.org/10.1190/1.1815648 Plain-Language Summary PDF DownloadLoading ...
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.026 |
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".