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Record W1972782687 · doi:10.1177/154193120004402617

The Contribution of Ergonomics to the Prevention of Musculo-Skeletal Lesions among Ambulance Technicians

2000· article· en· W1972782687 on OpenAlexaboutno aff
Rafat Massad, Christiane Gambin, Lisette Duval

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2000
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedical emergencyHuman factors and ergonomicsWork (physics)Manual handlingEngineeringPoison controlMedicineOperations managementMechanical engineering

Abstract

fetched live from OpenAlex

The Association pour la santé et la sécurité, secteur affaires sociales duQuébec (ASSTSAS) has worked with three ambulance companies to develop and implement a training program for Québec's ambulance technicians on patient handling strategies that are respectful of both the needs of the patients and the biomechanical limitations of the technicians. The lifting strategies used by the ambulance technicians to transfer patients from one surface to another were questioned and new strategies, based on sliding techniques, were developed. Further research is required to design ambulance equipment that is not only better suited to the patients' needs, but also more appropriate for the ambulance technicians' work, in order to help prevent workplace accidents.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.251
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207