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Record W3109948122 · doi:10.1177/1064804620975733

Footfall Deflection of Antifatigue Flooring During Simulated Human Stance

2020· article· en· W3109948122 on OpenAlexfundno aff
Jackie D. Zehr, Taylor B. Winberg, Andrew C. Laing, Jack P. Callaghan

Bibliographic record

VenueErgonomics in Design The Quarterly of Human Factors Applications · 2020
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeflection (physics)IndentationMaterials scienceShore durometerStructural engineeringComposite materialMathematicsEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

This study quantified the effect of compression load and duration on the deflection of five separate antifatigue flooring surfaces. Following standardized measurement of A Shore hardness, each sample underwent simulated single-leg stance indentation procedures that differed by compression load (45.3 kg, 90.7 kg, 136.1 kg) and duration (initial = 2.5 s, intermediate = 6.25 s, final = 12.5 s). Vertical deflection was compared across conditions, and the relationship between A Shore hardness and deflection was characterized. When compressed with 45.3 kg, deflection was not influenced by duration, but at 136 kg, deflection differed between durations by up to 15%. The relationship between A Shore hardness and deflection was characterized by a third-order polynomial function ( R 2 > 0.991).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.629

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 head0.065
GPT teacher head0.335
Teacher spread0.270 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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