Prediction of the color variation of moso bamboo during CO2 laser thermal modification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thermal modification is widely used for bamboo materials as an efficient modification method. CO2 laser with the advantages of high energy density, short process period, non-pollution, etc. could be applied as a novel thermal treatment for wooden and bamboo materials processing. The laser intensity argumentation of power, motion arguments of feed rate, and sweep width for laser emitter were selected as input arguments for treating the Moso bamboo surface. The lightness variation and total color variation (∆L* and ∆E*) were collected using a portable colorimeter to describe the bamboo surface color variation after laser irradiation. Response surface methodology was chosen for designing experiments and modeling. The results showed that the increase of laser power had a positive influence on increasing the absolute values of ∆L* and ∆E*, but the feed rate of laser emitter and sweep width increasing had opposite effects on absolute values of ∆L* and ∆E*. The quadratic models of ∆L* and ∆E* created by response surface methodology were competent for describing the relationship between laser processing arguments and color indexes of ∆L* and ∆E*. This approach will be useful for selecting suitable and desirable processing arguments to get the surface color of bamboo productions.
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.
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) | 0.000 | 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) | 0.000 | 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