Fines migration in sediments containing methane hydrate during depressurization
Bibliographic record
Abstract
This project presents the X-ray CT image sets obtained during depressurization of methane hydrate bearing sediments. Particularly, the imaging experiment aims on quantifying the extent of fines migration in sediments containing some fines due to depressurization. In this study, three sediments were tested as follows: (a) Ottawa 20-30 sand with 9%w/w silica silt (b) F110 sand with 11.5%w/w silica silt (c) F110 sand with 6%w/w kaolinite and 4%w/w silica silt. These three are referred to as Sample#1, Sample#2, and Sample#3 in the files. Each experiment was divided into four steps: 1. Gas injection 2. Hydrate formation 3. Water injection 4. Depressurization The details of this experiment can be found in the published paper below: Gyeol Han, Tae-Hyuk Kwon, Joo Yong Lee, and Timothy J. Kneafsey (2018) "Depressurization-induced fines migration in sediments containing methane hydrate: X-ray computed tomography imaging experiments", Journal of Geophysical Research - Solid Earth, DOI:10.1002/2017JB014988.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".