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Record W2955599881 · doi:10.1080/23335432.2019.1633958

The effect of intracortical bone pin on shoulder kinematics during dynamic activities

2019· article· en· W2955599881 on OpenAlexaff
Maryam Hajizadeh, Benjamin Michaud, Mickaël Begon

Bibliographic record

VenueInternational Biomechanics · 2019
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSagittal planeKinematicsCoronal planeMedicinePhysical medicine and rehabilitationScapulaOrthodonticsAnatomyPhysics

Abstract

fetched live from OpenAlex

Intracortical bone pins are introduced as gold standard for analysing skeletal motion because of eliminating soft tissue artefact. However, excluding this methodological error might be in cost of intervening movement pattern by local anaesthesia and pain of external tool within body. The purpose of this study was to examine whether intracortical bone pins alter shoulder joint kinematics or coordination. Three subjects were analysed during arm elevation/depression in frontal and sagittal planes. Retroreflective skin markers captured the motion in two sessions, before and after inserting bone pins (SKIN and PIN sessions), respectively. Thoracohumeral and scapulothoracic kinematics and scapulohumeral rhythm (SHR) were compared between two sessions. Thoracohumeral exhibited lower elevation and internal rotation in PIN session especially close to maximum arm elevation. The highest differences were observed for scapulothoracic kinematics, with higher retraction during abduction as well as higher posterior tilt, lateral rotation and retraction during flexion in PIN session. In addition, no systematic changes in SHR between subjects was found. Statistically significant lower SHR in PIN session was observed over 87-100% of thoracohumeral elevation/depression cycle in frontal plane and over 25-61% in sagittal plane. Further studies should treat carefully toward the clinical validity of shoulder joint kinematics after inserting bone pins.

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 score0.046
Threshold uncertainty score0.307

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 head0.006
GPT teacher head0.298
Teacher spread0.292 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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