The Desired Sensation Level Multistage Input/Output Algorithm
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Desired Sensation Level (DSL) Method was revised to support hearing instrument fitting for infants, young children, and adults who use modern hearing instrument technologies, including multichannel compression, expansion, and multimemory capability. The aims of this revision are to maintain aspects of the previous versions of the DSL Method that have been supported by research, while extending the method to account for adult-child differences in preference and listening requirements. The goals of this version (5.0) include avoiding loudness discomfort, selecting a frequency response that meets audibility requirements, choosing compression characteristics that appropriately match technology to the user's needs, and accommodating the overall prescription to meet individual needs for use in various listening environments. This review summarizes the status of research on the use of the DSL Method with pediatric and adult populations and presents a series of revisions that have been made during the generation of DSL v5.0. This article concludes with case examples that illustrate key differences between the DSL v4.1 and DSL v5.0 prescriptions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it