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Record W2025604369 · doi:10.1177/154193121005400602

Neck Biomechanics and Multiple Wide Computer Displays

2010· article· en· W2025604369 on OpenAlexaff
Matt Camilleri, Michael C. Bartha, Cynthia J. Purvis, David Rempel

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2010
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsHewlett-Packard (Canada)
Fundersnot available
KeywordsSagittal planeGazeRotation (mathematics)Head (geology)Computer scienceComputer visionArtificial intelligenceAnatomyMedicineGeology

Abstract

fetched live from OpenAlex

Computer workstations are increasingly being fitted with multiple large displays. Display placement influences head posture and neck symptoms but the effects of multiple displays are not well known. This study evaluated the placement of two wide displays over a large range of heights and distances. Twenty participants performed internet search tasks with the search window at thirty-six positions, defined by three distances from the eyes (50 to 86 cm), three gaze angles (0 to 28° below the eye horizon), and four lateral distances from the mid-sagittal plane (13 and 32 cm to the left and to the right). Motion capture equipment tracked head and neck postures and simulation software calculated muscular capacities. Regression analyses demonstrated significant ( p < 0.001) effects of gaze angle on neck flexion, lateral angle on neck rotation, and the interaction of gaze angle and lateral angle on neck lateral flexion. The moment generating capacities of the trapezius and splenius muscles, and the self-selected display positions, suggest that increases in wide display's field-of-view should be biased vertically (upward).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.739

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 head0.010
GPT teacher head0.237
Teacher spread0.228 · 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 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

Citations2
Published2010
Admission routes1
Has abstractyes

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Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicErgonomics and Musculoskeletal DisordersFrench-language works237,207