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Record W2024912943 · doi:10.1260/0263-0923.31.3.193

Helping Sufferers to Cope with Noise Using Distance Learning Cognitive Behaviour Therapy

2012· article· en· W2024912943 on OpenAlexaff
Geoff Leventhall, Donald Robertson, S. J. Benton, Lyn Leventhall

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2012
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsNoise (video)DistressPerceptionCognitionPsychologyNoise controlComputer scienceAudiologyMedicineArtificial intelligenceNoise reductionClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Unresolved noise complaints cause considerable distress to sufferers, and a deterioration in quality of life as a consequence of failure to cope with the noise stress. The environmental noise control structure is directed towards higher frequency noises, which can be assessed by use of A-weighted measurements and this results in some low frequency noise problems receiving an inadequate evaluation. A number of countries now have limits for low frequency noise, but these are not yet well known or widely used. (Leventhall, 2009). Is there a solution to the problem of what can be done to help the small number of people who are adversely affected by perception of a low frequency noise, which it has not been possible to control? This paper describes how Cognitive Behaviour Therapy can be a solution.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.352
Teacher spread0.322 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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