Interlist Equivalency of the Northwestern University Auditory Test No. 6 in Quiet and Noise with Adult Hearing-Impaired Individuals
Bibliographic record
Abstract
Abstract The purpose of the study was to determine the influence of sensorineural hearing loss and broadband noise on the interlist equivalency of the Northwestern University Auditory Test No. 6 (NU-6). There were two groups of participants: the first group consisted of 14 adults with mild-to-moderate hearing loss (mean age = 56 years; SD = 4.83); the second group consisted of 11 age-matched, normal-hearing individuals (mean age = 55 years; SD = 4.69). Each group heard the four lists of the NU-6 in quiet and in broadband noise at four signal-to-noise ratios (–10 dB, –5 dB, 0 dB, and +5 dB). The NU-6 stimuli were presented at 35-dB sensation level relative to each listener's speech reception threshold. Results indicated that, for both groups, there was a significant main effect for NU-6 list. Post hoc single degree of freedom contrasts revealed that this main effect was due to significant differences between some of the lists when presented in background noise. There were no differences between the lists in quiet. Because of the findings of differences between some of the lists in noise, the authors suggested that clinicians or researchers use caution when comparing scores obtained from two different NU-6 lists over time. That is, if scores from two lists are different, it is important for the clinician to determine whether this disparity is due to a change in word recognition ability or simply due to a difference between the lists. Abbreviations: NU-6 = Northwestern University Auditory Test No. 6, SNR = signal-to-noise ratio, SRT = speech reception threshold
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".