Bibliographic record
Abstract
Although still somewhat obscure and seldom utilized, hot melt grouts have for decades proven useful in stopping high magnitude inflows (Schonian & Naudts, 2003). In 2002, injection of hot bitumen in combination with low mobility and high mobility cement-based grouts succeeded in eliminating a 2205 ℓ /sec (35,000 GPM) inflow into the Lonestar Quarry in Cape Girardeau, Missouri. By 2002, quarrying at the site had been active for over 100 years and the quarry floor at the locus of the inflow was more than 100 metres lower than prevailing grade. The source of the inflow was the nearby Mississippi River. Two principal inflow pathways were identified, each of them large conduits measuring as great as 6 metres wide x 9 metres high and centered 76 metres and 93 metres below prevailing grade, respectively. Grouting holes were drilled on a line parallel to the quarry face, transverse to the strike of the inflow path and set back approximately 80 metres from the quarry face. Prior to hot bitumen grouting, several weeks and thousands of tons of cement were consumed attempting, unsuccessfully, to reduce the inflow. Once the program was eventually shifted to hot bitumen grouting, drilling and cement grouting operations were redirected to focus on flushing clean any sediment-filled, inactive features, and filling these with a competent grout in advance of the eventual hot bitumen grouting intervention. Concurrently, an array of new injection wells was drilled consisting of four hot bitumen injection wells, two low mobility cement-based grout injection wells and five high mobility cement-based grout injection wells, all for simultaneous use in a final assault on the inflow. This final assault, with hot bitumen injection playing the key role, succeeded in completely stopping the inflow within just seven hours of the start of grouting.
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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 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".