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Record W6989585927

Biomechanical comparisons considering risk to the lumbar spine: walking with no load, a backpack, and a person on the back

2015· dissertation· en· W6989585927 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typedissertation
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBackpackTrunkLumbarRepeated measures designBonferroni correctionRange of motionBiomechanicsTorso
DOInot available

Abstract

fetched live from OpenAlex

Participants were twelve 70+ kg male strength-trained athletes and one passenger child with a mass of 29 kg. The male participants walked three times over a force plate embedded in an eight metre walkway for each of three conditions: carrying no load, a 29 kg backpack, or a 29 kg passenger. Variables were compared using a repeated measures ANOVA test with a Bonferroni correction. Both load conditions produced compensatory trunk flexion; trunk flexion increased from no load to piggybacking to backpacking. Trunk range of motion was similar for no load and piggybacking, but increased to backpacking. The backpack load caused greater resultant and total magnitude of torque than the passenger load. The trunk extensors dominated with no load and piggybacking and the trunk flexors dominated with backpacking. Many of the significant differences between conditions suggest that piggybacking is biomechanically more similar to natural gait than is backpacking.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.066
GPT teacher head0.326
Teacher spread0.260 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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