Waste corn husk fibers for sound absorption and thermal insulation applications: A step towards sustainable buildings
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
In the last decade, noise pollution and global warming and their effects on human health and the environment have received much attention. Building sectors are one of the most important areas for potential improvements. To this end, sound-absorbing and thermal insulation construction materials are being used effectively. Recently, a great deal of interest has arisen in using various natural fibers as sound-absorbing and/or thermal insulation materials . In line with these studies, this work investigates the acoustic absorption and thermal insulation characteristics of corn husk fiber (CHF). The results showed that the samples enjoy excellent noise reduction coefficients of 0.36–60 and effective thermal conductivities of 0.038–0.042 W/mK. It was found that the thermal insulation properties of CHFs are not significantly influenced by the moisture content . The Dunn and Davern (DD) model and a modified model of DD based on the Nelder-Mead simplex algorithm were also used to predict the acoustic behavior of the samples. It was found that the proposed model provides very excellent prediction accuracy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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