Influence of water and lubricant fluids on peak strength of Queenston shale from southern Ontario
Bibliographic record
Abstract
The strength of Milton Queenston shale (MQS) before and after soaking in water and lubricant fluids (LFs) was examined. The investigated LFs (i.e., bentonite and polymer solutions) are utilized in the microtunnelling technique (MTT) to facilitate the installation of tunnel or pipe sections. To investigate the relevant mechanical properties of MQS under different wetting conditions, a series of laboratory tests including Brazilian split, uniaxial compression, and triaxial compression were carried out. These tests were performed on vertically and horizontally cored specimens with respect to the rock bedding. Fresh specimens (i.e., intact) and specimens soaked for 100 days in LFs and in water were examined. The 100 day period was selected, as it may reasonably represent the construction period where some swelling of the Queenston shale can occur. It was revealed that the strength of MQS substantially decreased after soaking. With greater impact in the vertical direction, both water and bentonite solution caused similar decrease in MQS strength of 23%–70%, while polymer solution caused a smaller decrease of 10%–57%. Accordingly, strength envelopes of MQS were established for vertical and horizontal directions before and after soaking.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".