IBANA-Calc Validation Studies
Bibliographic record
Abstract
This report compares measured and predicted indoor sound levels in buildings exposed to aircraft noise. Predictions were made using the IBANA-Calc software that was developed to make it easy and convenient to calculate indoor sound levels in buildings exposed to aircraft noise. This report is therefore a further validation of the IBANA-Calc software and an exploration of some of the details of the predictions and the differences between laboratory and field measurements of sound insulation. The work is the final component of the IBANA project (Insulating Buildings Against Noise from Aircraft) that included: (a) laboratory measurements of the sound transmission loss of building envelope components, (b) field measurements of a varied constructions of a test house at Ottawa Airport and (c) development of the IBANA-Calc software. Measurements reported here were made using multi-track recordings of indoor andoutdoor sound levels in buildings near Vancouver and Toronto Airports. These included new homes near Toronto Airport, an older home near Vancouver Airport and offices in a Vancouver Airport building. The sites were not ideal simple cases but included various complicating factors that made the predictions more challenging.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".