Estimation of reed flow signal from instrument performance.
Bibliographic record
Abstract
In this work we present a technique for estimating the reed flow signal, typically a periodic sequence of pulses, from the recorded sound of a reed instrument. The instrument is modeled as a reed coupled to a 1-D waveguide having unknown filter elements that must first be determined before constructing the instrument reed flow transfer function. As pressure waves make two round trips from the mouthpiece to the bell and back for each reed pulse, the output periodic pressure has two distinct halves: the second half being roughly the first half filtered by the instrument’s propagation losses. Estimation of these losses is not simply a spectral ratio, as the two halves are not temporally disjoint and the beginning of the reed pulse period is often unclear. The running autocorrelation of the recorded signal is zero phase and naturally provides the beginning of the period of the recorded signal as well as clear first and second phases that may be analyzed to estimate the round-trip losses in the instrument. Combining these losses with the direct measurements of the bell reflection function, a filter is developed which inverts the implied waveguide to produce the reed flow estimate.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".