Assessment of materials for gouging abrasion applications
Bibliographic record
Abstract
Various materials are used to resist wear in crushing and sizing equipment in mining and mineral processing. They include steels, white irons and hardfacing deposits. Within each of these classes there are a number of options available. Jaw crusher testing using a modified ASTM G81 procedure, has been carried out to assess the resistance of some of these materials to gouging abrasion. The method involves a comparison of the wear losses that occur for reference and selected test plates when a controlled amount of standard feed rock is comminuted in a laboratory jaw crusher. Materials evaluated are Q&T abrasion resistant (AR) plate steels, cast austenitic manganese steel, chromium and chromium molybdenum white irons as plain castings and in laminated forms, and also chromium carbide and tungsten carbide overlaid wear plates and hardfacing. In addition to obtaining a performance ranking for material selection purposes, the microstructural, compositional and hardness influences on gouging abrasion attack have been investigated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".