Post-Classification of Nominally Identical Steel-String Guitars Using Bridge Admittances
Bibliographic record
Abstract
Dynamic and acoustical measurements were conducted on 18 nominally identical acoustic guitars coming off the same production line and post-classified by the manufacturer as either bassy (i.e., with a more prominent bass response), mid-even (i.e., well-rounded and sounding even from string to string) or treble (i.e., with a brighter sound that cuts through the band).One goal was to find features of the guitar admittances that could be used to automatically classify them according to these categories.A second goal was to investigate whether experienced guitarists agreed with the classifications provided by the manufacturer.Physical properties were investigated independently and in conjunction with perceptual assessments by musicians collected during a classification task.Despite very low agreement across guitarists as well as between musicians and the manufacturer, results showed that the bassy guitars had a lower frequency for their breathing mode.This suggests a lower stiffness-to-weight ratio for the respective guitar bodies, which may be caused by small variations in the plate thickness or wood properties.The guitars characterized as treble in this study tended to have lower averaged mobility in the 600-2000 Hz range, which might suggest a weaker string-to-body coupling at those frequencies and/or a longer decay for higher partials, though these characteristics were not confirmed.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".