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Record W2159863266 · doi:10.1177/108471380500900402

The DSL Method for Pediatric Hearing Instrument Fitting: Historical Perspective and Current Issues

2005· review· en· W2159863266 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTrends in Amplification · 2005
Typereview
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
Fundersnot available
KeywordsDigital subscriber lineHearing aidAudiologyHearing lossPerspective (graphical)Computer scienceMedicineTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

The Desired Sensation Level (DSL) Method was originally developed in the early 1980s to provide clinicians with a systematic, science-based approach to pediatric hearing instrument fitting that ensures audibility of amplified speech by accounting for factors that are uniquely associated with the provision of amplification to infants and young children who have hearing loss. This review identifies and describes several of the primary factors that have been considered in the development of the DSL Method. Specifically, the issues discussed relate to: (1) the definition and measurement of relevant acoustic, electroacoustic and audiometric variables; (2) how the external ear acoustics of infants and young children are accounted for in the DSL Method for both audiometric assessment and in the fitting of amplification; and (3) how the DSL Method has evolved concurrently with developments in hearing instrument and electroacoustic measurement technologies. Finally, current issues in the field are identified that have motivated the development of version 5.0 of the DSL Method for hearing instrument fitting.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.236
GPT teacher head0.476
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it