Wear behavior of B<sub>4</sub>C reinforced Al 6063 matrix composite electrodes fabricated by stir casting method
Bibliographic record
Abstract
The objective of the present study was to predict the surface topological characteristics of Al–B 4 C composite electrodes and oil hardened, non-shrinking (OHNS) die steel in the electrical discharge machining (EDM) process. The surface characteristics of the composite electrodes were evaluated using a scanning electron microscopy (SEM) and EDAX analysis. The surface roughness and hardness of the OHNS die steel were measured using a Stylus probe and Brinell hardness tester, respectively. The composite electrodes were prepared with Al 6063 and B 4 C materials. In the stir casting process, the two materials were mixed at the molten state at different compositions. The chemical composition of the composite electrodes were analyzed by SEM and EDAX testing. The surface roughness of the OHNS steel was measured using a Brinell hardness tester. Based on SEM and EDAX results, 92% Al 6063, 8% B 4 C produced the best surface roughness in OHNS die steel.
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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 | 0.000 | 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) | 0.001 | 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".