MétaCan
Menu
Back to cohort
Record W1981411858 · doi:10.1055/s-2002-35875

Central Auditory System and Central Auditory Processing Disorders: Some Conceptual Issues

2002· article· en· W1981411858 on OpenAlexafffund
Dennis P. Phillips

Bibliographic record

VenueSeminars in Hearing · 2002
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAuditory systemAudiologyPsychologyMedicine

Abstract

fetched live from OpenAlex

The central auditory system has both parallel and hierarchical afferent architectures. In the frequency domain, it is tonotopically constrained, and in the spatial domain, it is dominated by a representation of the contralateral acoustic hemifield. The functions supported by the afferent pathways can be somewhat overlapping, and the connectivity among the pathways is to some degree plastic. Partial deafferentation (in the form of high-frequency hearing loss) and behavioral experience are capable of causing alterations in tonotopic maps in the more rostral auditory system, even in adult animals. Central auditory processing is often frequency-specific. The temporal processes needed for normal auditory function are diverse, which is to be expected given the heterogeneous ways in which auditory events are disposed in time and encoded neurally. Central auditory pathologies need not respect structural or functional boundaries in the brain, and so should be expected to have idiosyncratic presentations. Management strategies based on auditory training may exploit basic neuroplasticity, but more evidence is needed to substantiate any hypothesis of their differential efficacy in remediation of central auditory processing disorders or language and reading problems. KEYWORDS Auditory neuroscience - neural representation - neural plasticity - temporal processing - perceptual architecture - auditory training

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.264
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueSeminars in HearingSame topicHearing Loss and RehabilitationFrench-language works237,207