FREQUENCY SPECIFICITY OF NARROWBAND CHIRP AND 2-1-2 STIMULI: SPECTRAL ANALYSES
Bibliographic record
Abstract
Abstract Objective The current study examined the frequency specificity of NB chirps by comparing the spectral characteristics of 500-, 1000-, 2000- and 4000-Hz NB CE-Chirp ® LS stimuli with those of 2-1-2 tones. Design Spectral characteristics including the centre frequency, bandwidth, and stimulus energy changes after stopband filtering were compared. The bandwidth was computed as the difference between the upper and lower frequencies at -20 dB (& -3 dB) cutoff points of the main lobe; the centre frequency was determined as the geometric mean of the upper and lower frequencies at the -20 dB (& -3 dB) cutoff points. Results At 100 dB peSPL, the bandwidths of the 500-, 1000-, and 2000-Hz NB CE-Chirp ® LS acoustic spectra were 1.7-2.5 times wider than the acoustic spectra for the 2-1-2 tones; the 4000-Hz NB CE-Chirp ® LS bandwidths were 1.4-1.6 times wider than those of the 2-1-2 tones. The energy of NB CE-Chirp® LS stimuli was concentrated within ±0.75 octave of the centre frequency, compared to ±0.5 octave for 2-1-2 tones. Conclusion NB CE-Chirp ® LS stimuli demonstrated poorer frequency specificity compared with 2-1-2 tones. Further studies are needed to investigate the place specificity of the ABRs to NB CE-Chirp ® LS before implementing them clinically.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".