Application of alternative methods for determination of rock quality designation (RQD) index: a case study from the Rožná I uranium mine, Strážek Moldanubicum, Bohemian Massif, Czech Republic
Bibliographic record
Abstract
A comparison of rock quality designation (RQD) parameters obtained by drill core analysis and the RQD determined using alternative methods is presented using metamorphic rocks such as migmatized gneisses, migmatites, and amphibolites. Methods of borehole–wall imaging using high-resolution acoustic logging, optical televiewer, and simple video inspection as well as the structural analysis of exploration drift walls oriented subparallel to the analysed boreholes are used for alternatively evaluated RQD values. Results show that, in most cases, the RQD index measured directly on a drill core section reaches lower values (about 10%–30%) than the RQD evaluated by alternative methods. Significant differences in determination of the rock mass failure degree using classical and alternative methods may occur, especially in sections with higher frequency of the metamorphic foliation planes created by biotite-rich bands or by dark-coloured melanosome layers. The nature of biotite itself is favourable for the creation of pre-disposed jointing planes, in which the increased drill core disintegration caused by drilling technology or core handling can occur. Results show it is highly appropriate to make these comparisons on a larger scale and thus verify whether the observed differences affect the qualitative classification of the rock mass.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".