True North: A Comparison of Measured vs Modelled Noise Levels with iNoise
Bibliographic record
Abstract
Standard ISO 9613-2 [1] is a widely used standard in noise predictions for industrial noise. Various jurisdictions in Canada recommend or require the use of ISO 9613-2. The standard has been implemented in several commercialy available software suites that are in use in Canada today, e.g. CadnaA, Predictor and Soundplan. It has been noted that the translation of ISO 9613-2 in software algorithims can be open to interpretation [3], [4]. As a consequence, different software suites may produce different results for the same modelled situation. To help remedy this unwanted situation, Standard ISO/TR 17534-3 [2] was introduced in 2015. Recently, a new software suite has been introduced to the Canadian market, iNoise. iNoise looks and feels very similar to Predictor and is being marketed as a suite that strictly confirms to ISO 9613-2 in combination with ISO/TR 17534-3. Time for a reality check : how do noise levels that were predicted using iNoise compare to measured noise levels?
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".