Framework for evaluation of the relative contribution of the process on porosity–cutting force dependence in micromilling of titanium foams
Bibliographic record
Abstract
Porous titanium, characterized by interconnected and large open-cell structures, constitutes one of the most promising bone substitutes that are currently available for surgical orthopedic and dental implantation procedures. Since little is known about the behavior of this highly porous material during material removal operations, the main objective of this study was to develop a framework capable of evaluating the effect of cutting speed, cutting depth, and feed rate on the interplay between porosity and cutting force signatures, as experienced during microslot cutting experiments. The comparisons performed between optically determined porosity and cutting force profiles by means of standard random data analysis metrics (correlation coefficient, power spectral density, and coherence) revealed that the presence of a material discontinuity has a prevalent effect on cutting force variation in the case of micromilling processes characterized by (1) less intensive machining regimes and (2) larger cutter/workpiece engagement zones. The proposed methodology is useful in selection of the investigative approach to be taken in assessment of the micromachining-related behavior of highly porous foams subjected to micromilling operations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".