Some practical issues affecting repeatability and reproducibility in laboratory transmission loss tests
Bibliographic record
Abstract
The ASTM standard E90 defines the measurement of transmission loss, equivalent to the sound reduction index defined in ISO 10140. ASTM E90 and ISO 10140 specify requirements for the laboratory, the test procedure and conditions, and for preparation and mounting of the specimen under test. Despite the strict requirements in ISO 10140 and the somewhat less strict requirements in ASTM E90, transmission loss results for nominally identical specimens often vary if measured in different laboratories, and sometimes even if measured again in the same laboratory. In practice, there are many factors that affect the repeatability or reproducibility of a transmission loss test for a given specimen. This presentation will not attempt to systematically cover all different sources of uncertainty, but instead will highlight some practical issues commonly encountered in laboratory transmission loss tests. Examples will be presented for a number of issues, including the effect of leakage through the specimen under test, the effect of varying temperature and humidity in the test chambers, and the effect of re-using gypsum board.
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How this classification was reachedexpand
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 | 0.006 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".