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Record W4399307665 · doi:10.22374/jspv.v6isp1.19

CONCUSSION REHABILITATION INTERVENTIONS

2024· article· en· W4399307665 on OpenAlexvenueno aff
Jonathan Vincent, Kevin Kohmescher, Alec Mack, John Stout

Bibliographic record

VenueJournal of Sports and Performance Vision · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionRehabilitationPsychological interventionPhysical medicine and rehabilitationMedicinePhysical therapyPsychologyMedical emergencyPsychiatryInjury preventionPoison control

Abstract

fetched live from OpenAlex

Sports-related concussions (SRC) are a common injury among athletes. Despite our growing understanding of concussion pathophysiology, comprehensive rehabilitation programs remain a clinical challenge. The accepted view of SRC rehabilitation emphasizes physical and cognitive rest. However, some conflicting studies report rest may facilitate prolonged symptoms. In this review article, we report on alternative SRC rehabilitation strategies to address the complex symptom variations, including physical activity, neuro-visual training, vestibular training, music therapy, speech-language therapy, and hyperbaric oxygen chamber therapy. The mass of published works supports the utility of these alternative therapies to aid recovery, but more research is vital to clarifying these relationships. In this review, we explore the relationships between symptoms and therapies. As there is a growing body of evidence to support these alternative therapies, many questions remain when concerning the role these alternative methods play in the bigger picture of standardizing a thorough SRC rehabilitation program.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.003

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 head0.037
GPT teacher head0.388
Teacher spread0.351 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2024
Admission routes1
Has abstractyes

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