Specific Mixing Energy of Cemented Paste Backfill, Part I: Laboratory Determination and Influence on the Consistency
Bibliographic record
Abstract
Slump determination is widely used to assess the consistency and transportability of fresh cemented paste backfill (CPB). CPB consistency can depend on the mixing procedure for CPB preparation. In this paper, a method was developed to determine the specific mixing energy (SME) that is dissipated during the preparation of CPB mixtures and to analyze its effect on CPB consistency. For this purpose, CPB recipes were prepared using two tailings and the mixing parameters (mixing time and speed and load mass) were successively varied. SME was determined for each mixture using a power meter equipped with an energy recording system mounted on a laboratory Omcan mixer. Slump was also determined for each mixture. A semi-empirical model was then developed to predict SME as a function of the mixing parameters. Results showed that predicted SME compared well with measured SME during CPB preparation. Results also showed that slump increased with increasing SME. The influence of SME on the rheological and mechanical properties of CPB and practical applications are presented in a companion paper.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".