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Record W2748336118 · doi:10.1080/10803548.2017.1348056

Ergonomic evaluation of a new truck seat design: a field study

2017· article· en· W2748336118 on OpenAlexafffund
Michelle Cardoso, Fred Fulton, Colin D. McKinnon, Jack P. Callaghan, Michel J. Johnson, Wayne J. Albert

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2017
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité de MonctonUniversity of WaterlooUniversity of New Brunswick
FundersNew Brunswick Innovation Foundation
KeywordsTruckSittingEngineeringPhysical therapyCar seatSeat beltHuman factors and ergonomicsPoison controlAutomotive industryPhysical medicine and rehabilitationMedicineAutomotive engineeringMedical emergency

Abstract

fetched live from OpenAlex

A postural evaluation of commercial licensed truck drivers was conducted to determine the ergonomic benefits of a truck seat prototype in comparison with an industry standard seat. Twenty commercially licensed truck drivers were recruited to perform a 90-min driving task. Postures were assessed using accelerometers and a backrest and seat pan pressure mapping system. Subjective discomfort measurements were monitored using two questionnaires: ratings of perceived discomfort (RPD) and the automotive seating discomfort questionnaire (ASDQ). Participants reported significantly higher discomfort scores when sitting in the industry standard seat. Participants sat with more lumbar lordosis and assumed a more extended thoracic posture when seated in the prototype. Pairing the gluteal backrest panel with the adjustable seat pan also helped reduce the average sitting pressure on both the seat pan and the backrest. The prototype provided several postural benefits for commercially certified truck drivers, as it did for a young and healthy population.

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)0.002
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 score0.575
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0000.000
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 head0.077
GPT teacher head0.399
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

Citations11
Published2017
Admission routes2
Has abstractyes

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