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Record W4405496788 · doi:10.1155/2024/1449433

Guidelines for Returning to Dance Following Concussion: Adaptations From Sport Concussion Literature

2024· article· en· W4405496788 on OpenAlexaff
Sheyi Ojofeitimi, Lauren M. McIntyre, Elizabeth I. Barchi, Brittney Winnitoy, Jeffrey A. Russell

Bibliographic record

VenueInternational Journal of Clinical Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsCanadian Physiotherapy AssociationHeritage Medical Research Clinic
Fundersnot available
KeywordsMedicineConcussionDancePhysical therapyPhysical medicine and rehabilitationInjury preventionPoison controlMedical emergencyVisual arts

Abstract

fetched live from OpenAlex

Sport concussion receives substantial attention as a public health concern. Conversely, performing artists, including dancers, sustain concussions, but these aesthetic athletes do not receive the same level of consideration nor care for this injury as that offered to traditional athletes. The concussion literature pertaining to dance is sparse, and, to our knowledge, no recommendations exist for the crucial aspect of care related to returning to dance following a concussion. The purpose of this article is to assimilate the current knowledge about post‐concussion return to activity management in sport—the closest analog of the physical demands required in dance—as a means to delineate a framework for returning to dance following a concussion. Specific guidance is provided based on a review of evidence‐based practice so clinicians can ensure that dancers return safely to both their dance activity and any academic work they are required to undertake. Concussion in dance is not an infrequent occurrence and dancers and healthcare practitioners alike will benefit from dance‐specific guidance for returning to dance post‐concussion. Overall, the principles that form the foundation for return‐to‐sport decisions are remarkably robust for application to dance.

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)0.004
metaresearch head score (Gemma)0.077
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.077
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.294
GPT teacher head0.594
Teacher spread0.300 · 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.

Study designNot applicable
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

Citations4
Published2024
Admission routes1
Has abstractyes

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