A comparison of various steel-string acoustic guitars’ modal response with relation to typical playing styles
Bibliographic record
Abstract
Steel-string acoustic guitars are built with large variations in geometry and materials, leading to different-sounding instruments. Musicians will have preferences for geometries or woods depending on certain musical styles or personal preferences regarding tonal characteristics. For example, dreadnought-style guitars with either mahogany or rosewood back and sides and a spruce top are overwhelmingly preferred for bluegrass music. This work presents the beginnings of a project to collect measurements from a vast and varied collection of guitars attempting to span the ranges of guitar woods and geometries. Vibration and acoustic measurements of the instruments are captured and modal analysis is performed to extract the modal frequencies, damping ratios, and amplitudes of the prominent modes. The modal characteristics among them are compared to better understand the most prominent differences with an attempt to learn why certain geometries or woods are preferred for specific genres of music and playing styles. The dataset is continuing to grow and currently includes measurements of twenty different guitars.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".