One-side cutting strategy for ultraprecise single point cutting of v-grooves case 2: constant cutting area
Bibliographic record
Abstract
The current study presents a cutting strategy to be used during V-groove fabrication through ultraprecise single point cutting. The profile of the groove is produced by maintaining a constant cutting area. The experimental results suggest that a correlation between the amount of material removed in each pass and the magnitude of FY exists. However, while from a theoretical standpoint it is reasonable to predict that FY will remain constant since it is directly proportional with the amount of material removed (of a preset constant cutting area), a certain amount of decay in the magnitude of FY was noticeable. This might suggest that the gradually decreasing chip thickness also plays an unforeseen but possibly important role on the cutting force magnitude. In addition, surface topography measurements have confirmed that the proposed strategy can produce ultraprecise surfaces. The analysis presented in the current study sets the foundation for further development of future and more efficient cutting strategies to be used in ultraprecise single point cutting of V-grooves. Furthermore, simulation models of the cutting mechanics will be developed and then validated against the experimentally acquired results.
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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 | 0.001 | 0.000 |
| 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".