MétaCan
Menu
Back to cohort
Record W1986472792 · doi:10.1080/001401300404661

Metabolic cost and subjective assessment of palletizing and subsequent recovery

2000· article· en· W1986472792 on OpenAlexaff
Shrawan Kumar, Eugene C. Lechelt, Yogesh Narayan, Karen Chouinard

Bibliographic record

VenueErgonomics · 2000
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMetabolic costHeart ratePerceived exertionMetabolic rateMedicineMathematicsAnimal sciencePhysical medicine and rehabilitationEndocrinologyBlood pressureBiology

Abstract

fetched live from OpenAlex

Twenty-one male blue collar workers repeatedly lifted (palletized) a box weighing 22 kg six times min(-1) for 5 min to a shelf of fixed height. The experimental conditions included two planes of lifting (symmetries), two shelf clearances, and three headrooms. The metabolic (heart rate, caloric cost and ventilation volume) and psychophysical variables (rate of perceived exertion, RPE; visual analogue score, VAS; and body part discomfort ratings, BPDR) were measured during resting, palletization, and recovery phases. In palletization the heart rate and metabolic cost ranged between 25 to 35% of the maximal aerobic capacity. Of the three factors only headroom had a significant effect on metabolic cost (p<0.02) and the BPDR for low back (p<0.05). In the recovery phase only headroom had significantly effect (p<0.001) on metabolic cost. The metabolic recovery took 10 min; however, recovery measured through psychophysical indices appeared to continue for 20 min.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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

Citations9
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueErgonomicsSame topicSports Performance and TrainingFrench-language works237,207