Pore Characteristics Analysis of Shale from Sichuan Basin, China
Bibliographic record
Abstract
Pore characteristics are significant for shale gas exploration and production. In this paper, the method of field emission scanning electron Microscopes (FE-SEM) was applied to qualitatively describe minerals and pore structures of shale samples. Low pressure nitrogen adsorption-desorption and carbon dioxide adsorption were applied to analyse meso-pores and micro-pores respectively. Inter-particle pores are always associated with rigid mineral grains and intra-particle pores are mainly located in unstable minerals. The BET (Brunauer–Emmett–Teller) surface area of Longmaxi Formation (LMX) is 5.47m 2 /gr and 16.33m 2 /gr of Wufeng Formation (WF). N 2 and CO 2 adsorption shows that the diameter of micro-pores in the LMX and WF formation is approximately 1nm. Most meso-pores in WF formations range from 2nm - 20nm, while meso-pores existing in LMX formations range from 2nm - 30nm.
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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 | 0.002 | 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 | 0.000 |
| 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".