On the optical efficiency of collecting scattered radiation or telescopically imaging the measurement area in airborne acoustic pressure evaluations
Bibliographic record
Abstract
Photon correlation is an optical method for calculating acoustic pressures through particle velocity measurements, involving the intersection of two focused Gaussian beams forming an interference fringe pattern. Particles within this measurement region exhibit sinusoidal motion as a result of a propagating acoustic pressure wave over the fringes, consequently scattering photons. This scattered radiation is then collected and processed to determine the particle velocity and then the acoustic pressure. In order to analyse the efficiency of the optical collection system, decoupled optical delivery configurations were implemented. In this case, instead of relying on particles moving over static fringes, moving fringes can be made to pass over an apparently static particle. To simulate this effect, a single laser beam can be modulated with a 3-D printed pattern simulating sinusoidal particle motion across fringes. Having established this alternative delivery system, suitable optical collection systems can be implemented, so that their efficiency can be analysed and assessed. This paper reports on the details of two such collection systems; analysing spherically propagated radiation and telescopically capturing the measurement area respectively.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".