Development of the primary standards system based on the optical method for airborne ultrasound range
Bibliographic record
Abstract
Non-invasive absolute measurement methods based on optical methods are being considered to be potential new primary standard systems for airborne acoustics. These methods mainly based on methods to measure acoustic particle velocities, utilize photon correlation or interferometry. Recently, it has become necessary to observe the possibility of expanding these methods to airborne ultrasound, because of increasing number of applications related to airborne ultrasound range. In this study, the factors necessary to expand the range of primary system based on photon correlation method to the low ultrasonic frequency range were considered. The basic problems with the measurement system for this purpose are related to measurement system, sound source, and problems induced with the artifact (also referred to as device under test) setup. Regarding the measurement system, system design parameters to expand the lower bound of sound pressure were investigated, in addition to the suitability of the method to enhance the photon count signal by applying the phase resolved method. In addition, the feasibility of applying the synchronizing method to resonant and pulsar type sound sources to obtain sufficient sound pressure in the ultrasonic band was observed. In addition, signal processing procedures to remove the effect of specular reflection that occurs when calibrating a microphone were investigated. [Work supported by the Korea Planning & Evaluation Institute of Industrial Technology (RS-2022-00154837).]
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".