Analysis of overlapping rate of spot derived from ablated monocrystalline silicon by femtosecond laser
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Bibliographic record
Abstract
In order to investigate the overlap rate of an ablated spot on monocrystalline silicon by a femtosecond laser, a skewness spot derived from plasma is analyzed. First, the serial spot image is collected, and the ablated core area of the spot is extracted by the way of bit image layering so that the peripheral halo can be eliminated effectively. The image of the spot is enhanced by Gaussian-guided filtering, which has the effect of keeping the edge of the spot; the smoothness of different directions is the same, and the gray distribution is more uniform. Second, the two-domain product gray centroid method is introduced to extract the spot centroid; at the same time, considering the information of spatial domain and value domain, the standard deviation is reduced by1.0. Third, according to the characteristics of spot shape change, the centroid coordinates are tracked by the Kalman filter optimized by wavelet heteropoly denoising, and the error is reduced by 0.5. Finally, the distance proportion sum method is introduced to calculate the diameter of the deflection spot, and then, by using the optimal tracking method, the average change in speed of the spot in the transverse direction is found to be 0.07 mm/s. The result of this paper shows that, on the one hand, with the increase of laser power, the influence factor of spot deflection on the spot diameter is increasing but the increase in the amplitude is gradually reduced. It can be seen that the increase of laser power can slow down the influence of spot deflection on spot overlap. Between 10 and 20 mW, strong increasing effect is shown; however, between 20 and 50 mW, a weak increasing effect is shown. On the other hand, strictly speaking, it is not the scanning speed but the actual ablation speed that has a direct impact on the spot overlap rate.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it