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Record W1220836320 · doi:10.3233/oer-2004-4103

Estimation of load transfer force to the hands during sagittal plane box lifting

2004· article· en· W1220836320 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOccupational Ergonomics · 2004
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsQueen's UniversityLaurentian University
Fundersnot available
KeywordsTransfer (computing)Sagittal planeLift (data mining)KinematicsSimulationMathematicsStructural engineeringComputer scienceEngineeringPhysicsMedicine

Abstract

fetched live from OpenAlex

Load transfer force to the hands was investigated to provide an accurate estimate of load transfer during sagittal lifting tasks for application in an industrial setting. The effects of gender, load mass, lift style, load transfer duration and participant strength were examined as possible variables to improve the estimation of load transfer force. Ten healthy men and eleven healthy women completed a total of 25 box lifts using a freestyle technique. Kinematic data were collected using the OPTOTRAK™ and a portable video camera. Measured load transfer force (MLTF) was determined as the total load weight minus measured values from a force plate. Five methods of estimating load transfer to the hands were calculated and compared with MLTF. The enhanced load transfer force method (ELTF) of estimating load transfer to the hands was superior to all other estimation methods.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.337

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 head0.009
GPT teacher head0.214
Teacher spread0.205 · 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