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Record W3193834274 · doi:10.21834/ebpj.v6i17.2872

Solvent-Induced Hearing Loss from Occupational Exposure In Asia – A systematic review

2021· review· en· W3193834274 on OpenAlexaff
Mohd Shukri Mohd Aris, Ainul Naqueah Zainal Abidin, Ailin Razali, Norazura Ismail, Adrián Fuente

Bibliographic record

VenueEnvironment-Behaviour Proceedings Journal · 2021
Typereview
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversité de Montréal
FundersInternational Islamic University MalaysiaUniversidad Nacional de Luján
KeywordsHearing lossNoise-induced hearing lossSolvent exposureAudiologyPure tone audiometryLicenseSensorineural hearing lossMedicineAudiometryPsychologyNoise exposureEnvironmental healthOccupational exposureComputer science

Abstract

fetched live from OpenAlex

Exposure to certain solvents in the workplace can cause hearing loss. This study aims to bring attention to the existing literature on the adverse effects of solvents on workers' auditory function in a diverse Asia occupational setting. The literature search used in this study is PubMed and Web of Science. 87% of the selected studies reported that the highest prevalence of hearing loss was from solvents plus noise-exposed group. Evidence shows that interaction between the solvent and the noise could be both additive and synergistic. More epidemiology studies on solvent-induced hearing loss using diverse approaches are warranted in Asia region. Keywords: hearing loss, organic solvent, pure tone audiometry, chemical-induced hearing loss eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6i17.2872

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.093
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.098
GPT teacher head0.408
Teacher spread0.310 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2021
Admission routes1
Has abstractyes

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