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Record W70659692

Evaluation of the reliability of an ergonomic decision system.

2006· article· en· W70659692 on OpenAlexaboutno aff
Derek Ian. Dawson

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2006
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)Reliability engineeringComputer scienceRisk analysis (engineering)EngineeringForensic engineeringBusiness
DOInot available

Abstract

fetched live from OpenAlex

A novel approach deemed the Ergonomic Decision System (EDS) was designed to address the physical requirements of modern industry. The EDS, as the name implies, is a system that uses a series of questions and resulting choices to determine the path to the most appropriate ergonomic analysis tool for a given occupational task. The face validity of the EDS has been established through an extensive review of literature. Reliability was evaluated both within and between subjects. In two facilities, 6 Jobs were chosen based upon both injury and illness data and the differing physical requirements of each. These Jobs were video recorded and two Jobs were randomly chosen. Novice subjects (N = 6) were asked to apply the EDS to one of these jobs prior to being provided the basic ergonomic training. Subsequently, all trained subjects (N = 12) applied the EDS to the same 6 recorded Jobs. The results from the EDS applications were then compared to a criterion measure resulting in a total EDS score which was used to determine subject accuracy. A high overall mean accuracy value of 88.4%, was found with experts and novices varying only slightly with mean scores of 92.6% and 84.3%, respectively. Further, a consensus count was taken from each user for each condition to determine consistency. A good overall mean consensus, between subjects, of 76.9% was found with experts scoring 85% and novice subjects 72%. Also, the results of the pre-post training study indicated strong within subject consensus with an average of 88.9% across novice subjects. Finally, after a minimum of two weeks had passed, all subjects applied the EDS to the second randomly chosen Job. Results of the test-retest condition showed good consensus within subjects with a mean of 94.4%, where experts scored 88.9%, and novice subjects showed perfect consensus. The results of the study effectively establish that the EDS provided sufficient subject consistency and accuracy in directing subjects to the most applicable ergonomic resource across Jobs tested.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .D39. Source: Masters Abstracts International, Volume: 45-01, page: 0435. Thesis (M.A.Sc.)--University of Windsor (Canada), 2006.

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)0.012
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.076
GPT teacher head0.370
Teacher spread0.293 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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