Architectural acoustics and noise control studies at the University of Nebraska's Architectural Engineering program
Bibliographic record
Abstract
The University of Nebraska–Lincoln (UNL) instituted an Architectural Engineering (AE) program in 1999 and celebrated its 25th anniversary last year. Currently, there are only 39 ABET-accredited AE programs around the world, and very few of these include acoustics as a primary area of study in their curricula. Based in the city of Omaha, the Nebraska AE program has trained students in architectural acoustics and noise control from the program’s inception, offering opportunities to study acoustics within its multiple degree options (Bachelor of Science in Architectural Engineering, Master of Architectural Engineering, Master of Science in Architectural Engineering, and Doctor of Philosophy in Architectural Engineering). This presentation reviews the UNL AE program’s current acoustic courses, research interests, and facilities. Also highlighted are program alumni from the past quarter century. One unique aspect of the Nebraska AE program is that it is the only program to have received the $25 000 grand prize from the National Council of Examiners for Engineering and Surveying (NCEES) Engineering Education Award multiple times in the past decade.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".