Using the Box-Behnken experimental design to improve the biocompatibility of the powder Ti–TiB2 composite through laser surface treatment
Bibliographic record
Abstract
: The paper deals with the surface functionalization of a biocompatible powder-based composite Ti-TiB 2 prepared by spark plasma sintering, applying the fiber nanosecond laser working at 1064 nm wavelength in an ambient atmosphere. The influence of the laser pulse energy (E P ), laser beam spot overlap (O L), and laser beam trace overlap (O T ) on the integrity of the laser-treated surfaces was studied using the Box-Behnken experimental design (BBD) in order to maximize the surface osseointegration-relevant properties. The SEM analysis, surface roughness measurement, energy-dispersive X-ray spectroscopy, static contact angle measurement, and X-ray diffraction analysis were conducted to identify the surface topography, morphology, chemistry, and wettability. Finally, the multiple analysis of variance (ANOVA) and RSM methodology were performed to optimize the laser treatment parameters. Applying the second-order polynomial model, the optimal combination of process parameters was set as follows: E P = 0.3 mJ, O L = -12%, and O T = 40%. The confirmation test showed very high prediction accuracy of the surface roughness and chemistry but low prediction accuracy of the surface wettability.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".