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Record W4411874802 · doi:10.1016/j.apergo.2025.104587

Adaptations to fatigue during a repetitive multiplanar lifting task

2025· article· en· W4411874802 on OpenAlexafffund
Emma J Ratke, Dennis J. Larson, Michael W.R. Holmes, Shawn M. Beaudette

Bibliographic record

VenueApplied Ergonomics · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of WaterlooBrock University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTask (project management)Physical medicine and rehabilitationMedicineComputer scienceEngineeringSystems engineering

Abstract

fetched live from OpenAlex

Warehouse workers are often required to perform physically demanding repetitive lifting tasks leading to fatigue. Previous research has primarily focused on constrained lifting tasks when investigating fatigue. The purpose of the current study was to investigate fatigue-based movement adaptations during a multiplanar, ecologically relevant lifting task. Participants (n = 28) lifted, transferred, and lowered a mass continuously for 60 min. Full body kinematics and muscle activity of the lumbar erector spinae, rectus abdominis, external oblique, and anterior deltoids were collected continuously. Results suggest that the load moment arm decreased across the trial (4% decrease), and participants tended to complete movements faster (4% decrease). Further, participants exhibited less variability in thorax-pelvis flexion deviation phase when fatigued (9% decrease). Finally, rectus abdominis activity increased (4%MVIC increase), while anterior deltoid activity decreased over time (2% decrease). These behavioural, coordination-based, and muscular adaptations to fatigue all have potential implications for injury risk in repetitive lifting tasks.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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