Introduction to special section: Recent advances in reservoir characterization
Bibliographic record
Abstract
PreviousNext No AccessInterpretationJust-Accepted ArticlesIntroduction to special section: Recent advances in reservoir characterizationAuthors: Runhai FengDongfang QuSatinder ChopraSixue WuAndrey KlimushinKlaus MosegaardChingWen ChenKenneth BredesenRunhai FengAramco Asia, China. E-mail: [email protected]., Dongfang QuRamboll, Denmark. E-mail: [email protected]., Satinder ChopraSamiGeo, Canada. E-mail: [email protected]., Sixue WuBP, UK. E-mail: [email protected]., Andrey KlimushinRFD, USA. E-mail: [email protected]., Klaus MosegaardUniversity of Copenhagen, Denmark. E-mail: [email protected]., ChingWen ChenGeophysical Insights, USA. E-mail: [email protected]., and Kenneth BredesenGEUS, Denmark. E-mail: [email protected].https://doi.org/10.1190/int-2024-0603-spseintro.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookTwitterLinked InReddit FiguresReferencesRelatedDetails Just-Accepted ArticlesPages: 1-47ISSN (print):2324-8858 ISSN (online):2324-8866 publication data© 2024 Society of Exploration Geophysicists and American Association of Petroleum GeologistsPublisher:Society of Exploration GeophysicistsAmerican Association of Petroleum Geologists HistoryPublished Online: 04 Jun 2024 CITATION INFORMATION Runhai Feng, Dongfang Qu, Satinder Chopra, Sixue Wu, Andrey Klimushin, Klaus Mosegaard, ChingWen Chen, and Kenneth Bredesen, (), "Introduction to special section: Recent advances in reservoir characterization," Interpretation 0: 1-2. https://doi.org/10.1190/int-2024-0603-spseintro.1 Plain-Language Summary PDF Download Metrics Loading ...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".