Improving Pore Network Imaging & Characterization of Microporous Carbonate Rocks Using Multi-Scale Imaging Techniques
Bibliographic record
Abstract
Abstract Epoxy-pore casting is widely used to characterize geological samples. In this study, we present a robust pore imaging approach that applies Confocal Laser Scanning Microscopy (CLSM) to obtain high resolution 3D images of etched epoxy-pore casts of highly heterogeneous carbonates. In our approach, we have increased the depth of investigation for carbonates 20-fold, from 10 μm reported by (Fredrich, 1999; Shah et al., 2013) to 200 μm. In addition, high resolution 2D images from scanning electron microscopy (SEM) have been correlated with the 3D models from CLSM to develop a multi-scale imaging approach that covers a range of scales, from millimeters in 3D to micrometers in 2D. The developed approach was implemented to identify various pore types, e.g., the inter-crystalline and intra-granular microporosity, and the inter-boundary sheet pores in the limestone and dolomite samples.
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 | 0.000 |
| 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".