Robotization of “<i>in situ</i>” acoustic measurements
Bibliographic record
Abstract
Currently, “in situ” acoustic measurements require a high level of human involvement. Measurements are carried out by technicians or engineers, and most of the time, two people are required. MJM Acoustical Consultants Inc. has explored the possibility of using an autonomous and semi-autonomous robotic solution to assist in the measurement process. Developed in partnership with university Polytechnique Montreal, the research project consists of developing a software platform and hardware for a mobile robot capable of moving around, locating itself and performing measurements using a Type I sound level meter. The prototype generates its own local area network (LAN), making it possible to send commands through high-density partitions such as brick walls or concrete floors remotely from a laptop. Localization system such as a laser remote sensing system allows the robot to navigate around obstacles. Its low noise level when stationary makes it ideally suited to conduct common standard tests such as impact noise isolation, airborne sound attenuation between rooms and background noise level measurements. Through tests carried out on field sites, the solution developed constitutes an effective instrumentation to make acoustic measurements sessions more efficient with a reduced level of human operation.
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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 | 0.001 | 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) | 0.000 | 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".