Turbulent particle flux measurement with pulse-coherent Doppler sonar
Bibliographic record
Abstract
The accuracy of velocity estimates from pulse-coherent acoustic Doppler systems is related to the magnitude, R, of the ensemble-averaged complex pulse-pair correlation. The closer R is to unity, the more accurate the estimate. The accuracy of particle concentration estimates is also related to the value of R but, in contrast, high accuracy requires R to be less than unity, i.e., the amplitudes from individual pulses in an ensemble should be independent, in order to beat down Rayleigh statistics associated with configuration noise. Consequently, when estimating the turbulent component of the particle flux, i.e., the product of the particle concentration and velocity fluctuations, a tradeoff arises between these conflicting requirements for velocity and concentration accuracy. This tradeoff is investigated through a statistical model of sound scattering from particles embedded in idealized turbulence, and laboratory experiments in which particle velocities in turbulent flow are measured both acoustically, via pulse-coherent sonar, and optically, using particle imaging velocimetry.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".