Color change of Chinese fir through steam-heat treatment
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
Dark brown wood color is a current trend and widely appreciated by consumers in the furniture and decoration markets. Heat treatment is one of the most effective methods to darken wood’s appearance. The influence of steam-heat treatment on color change of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) was investigated within the temperature range from 170 to 230 °C and time from 1 to 5 hours in an air-tight chamber within an atmosphere comprising less than 2 percent oxygen. Saturated steam was used as a heating medium and a shielding gas. The results showed that the chroma difference (△C*) decreased gradually, while the color difference (△E*) and hue difference (△H*) increased with an increase in temperature and length of time. An analysis of variance (ANOVA) and a multi-comparison analysis revealed that the treatment temperature plays a more important role in darkening wood color during the process of steam-heat treatment in comparison with the treatment time. The results suggest that a more desirable wood color can be achieved with the technology of steam-heat treatment.
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