Experimental Determination of Sound Transmission Loss of Some Wood Species
Bibliographic record
Abstract
Aim of study: To determine the sound transmission losses of 16 different wood species with the different density in the range of 100-1000 Hz frequencies, and the relationship between density and transmission loss was. Material and methods: In this study sound transmission loss values of Ash (Fraxinus excelsior), Acacia (Robinia pseudoacacia L.), Beech (Betula pendula), Black pine (Pinus nigra), Black poplar (Populus nigra), Canadian poplar (Populus x euramaricana), Chestnut (Castanea sativa Mill.), Cypress (Cupressus sempervirens), Oriental beech (Fagus orientalis Lips,) Eucalyptus C. (E, camaldulensis Dehnh), Eucalyptus G. (Eucalyptus grandis), Juniper (Juniperus excelsa), Plane (Platanus orientalis L.), Scotch pine (Pinus sylvetris L), Turkish Red pine (Pinus brutia Ten) and White Oak (Quercus alba) wood specimens were determined by using the impedance tube kit. Main results: Sound transmission loss is observed in lower density wood material species with the increasing frequency. However, a clear relationship has not been established between the mean sound transmission loss and density. Highlights: It is important to determine the frequency-related acoustic performance parameters of the wood material and to its relationship with density.
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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 | 0.000 | 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) | 0.003 | 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 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".