Practical application of a tri-axial intensity array
Bibliographic record
Abstract
Sound intensity is a vector quantity representing the magnitude and direction of propagating energy within an acoustic field. In an underwater environment, a single omni-directional hydrophone can be used to measure instantaneous acoustic pressure and a finite difference approximation applied to the pressure signals from a pair of such hydrophones can be used to calculate particle velocity in a single direction. Because the time average of the product of instantaneous pressure and particle velocity is intensity, a pair of hydrophones is all that is required to measure a single component of the intensity vector. The complete three-dimensional intensity vector can be calculated using three orthogonal pairs of hydrophones. To evaluate this concept a tri-axial array consisting of three orthogonal pairs of omni-directional hydrophones has been developed and tested on both calibrated sources at a laboratory facility and sources of opportunity during sea trails in littoral waters. The use of this array to calculate the intensity vector and thereby localize both near-field and far-field acoustic sources and characterize the directionality of ambient noise fields will be discussed. The impact of signal-to-noise ratio and the effect of self-noise will also be examined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".