Pore-Scale Observation Of Residual Oil In Low Salinity Surfactant Flooding: The X-Ray Computed Tomography Images
Bibliographic record
Abstract
The results of analysis of the uploaded binary image sets have been already published in: Khanamiri, H. H., Torsæter, O., Stensen, J. Å. "Pore-Scale Observation of Residual Oil in Low Salinity Surfactant Flooding", presented at the Symposium of the Society of the Core Analysts, St. Jones, Canada, Aug 2015. The paper is available for download at http://www.jgmaas.com/SCA/2015/SCA2015-053.pdf The zip file is a collection of 6 data sets numbered from zero to five. Name of the data set after the number indicates the step of the injection experiment the data set represents. Data set zero represents the structure of the porous rock (dry scan). In addition, the expression inside the parentheses at the end of the name is the same as what has been used in the above-mentioned paper, particularly in the figures.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".