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Record W1981748177 · doi:10.1080/14639220701507398

Are males and females similarly consistent in their respective lifting patterns?

2008· article· en· W1981748177 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

VenueTheoretical Issues in Ergonomics Science · 2008
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTask (project management)Multivariate analysis of varianceConsistency (knowledge bases)KinematicsMotion (physics)Set (abstract data type)Work (physics)PsychologyMultivariate analysisMultivariate statisticsAnalysis of variancePhysical medicine and rehabilitationMathematicsStatisticsComputer scienceEngineeringArtificial intelligenceMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to assess the reproducibility of a lifting motion and whether there is a gender difference in terms of a consistent performance. Thirty-four healthy inexperienced males and females performed a lifting task of a load that was 20% of their personal lifting capacity on four separate testing days, while an electromagnetic motion tracking system recorded the lifting motion. All kinematic data were analysed with a mixed two-factor repeated measures multivariate ANOVA (gender × day) design. There were no significant day or gender differences indicating consistency exists in the lifting pattern. It is expected that individuals will adapt their lifting pattern to meet the needs of the lifting task. Given that the pattern was consistent over time for a specific task, it suggests a set motor pattern may be established. This knowledge has implications for work assessment strategies and training programmes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
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 head0.029
GPT teacher head0.308
Teacher spread0.279 · 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