Bibliographic record
Abstract
The impact of bit-coal/rock interaction during the cutting process in underground mines is great concern to the mining community of the world. Rock/coal cutting bears directly on rock/coal dust generation that causes "black lung/silicosis" in miners. On the other hand, rock cutting generates radiance of sparks that has potential to cause face ignition. Bit wear affects productivity, safety and economy. Hundreds of face ignitions and millions of dollars in productivity and compensation for respirable rock/coal dust related diseases are attributed to the cutting action of continuous miners/shearers. These undesirable impacts could be minimized by proper selection of bit types, bit design, cutting parameters of the cutting head, and amount of water and position of water jets. This thesis evaluates the effects of bit geometry in multiple bits---rock interaction, utilizing an automated rotary coal cutting simulator (ARCCS) and synthetic rock. Five types of bit/cutting tool with different cone and tip geometry were tested against the synthetic rock of 16&inches; x 14&inches; x 4&inches; dimension. The rotation of the cutting drum was kept at 100 rpm and the cutting drum was advanced at 0.14 in/sec of advance. Cutting force, penetration force, rate of advance and respirable dust were measured during the cutting process. Specific energy and specific dust were also calculated for each experiment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".