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Record W2509296789 · doi:10.4236/ojapps.2016.68053

Influence of Occupational Noise Exposure on Cognitive Ability of Grinders

2016· article· en· W2509296789 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Journal of Applied Sciences · 2016
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentCognitionNoise (video)BeijingAffect (linguistics)AudiologyStatisticsMedicinePsychologyEnvironmental healthMathematicsCognitive impairmentGeographyComputer scienceCommunicationArtificial intelligencePsychiatry

Abstract

fetched live from OpenAlex

Purpose: To investigate whether long-term noise exposure affects the cognitive ability of grinders. Methods: Cumulative noise exposure (CNE) and LAeq.8h determination were used to characterize the level of individual noise exposure; the Montreal Cognitive Assessment (MoCA) test (Beijing version) was used to evaluate cognitive function. Results: We compared the basic situation of workers in different groups and individual noise exposure intensity of grinders was monitored. Multiple linear-regression analysis was made and score of MoCA in different group was finally drawn. Conclusion: CNE and total score of MoCA have the relationship of negative correlation (r = -0.303, p < 0.05) which means long-term occupational noise exposure can affect the cognitive ability of grinders.

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)0.003
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 score0.503
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.082
GPT teacher head0.439
Teacher spread0.357 · 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