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Record W2118501767 · doi:10.1007/s11932-996-0006-3

Current concepts in concussion rehabilitation

2004· review· en· W2118501767 on OpenAlexaff
Karen M. Johnston, Gordon A. Bloom, Jim Ramsay, James Kissick, David Montgomery, Dave Foley, Jen‐Kai Chen, Alain Ptito

Bibliographic record

VenueCurrent Sports Medicine Reports · 2004
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsRehabilitationConcussionAthletesMedicinePhysical medicine and rehabilitationPhysical therapyProcess (computing)Poison controlInjury preventionMedical emergencyComputer science

Abstract

fetched live from OpenAlex

Active rehabilitation of sport injuries is a concept familiar to athletes and those caring for them. Rehabilitation goals aim to optimize recovery efficiency and diminish chances of repeat injury. Rehabilitation programs take many aspects of recovery and wellness into consideration including physical, social, and psychologic components. Ultimately, this is important in the recovery process after concussion. In this article we introduce the largely unexplored concept of multidimensional concussion rehabilitation and discuss physical, psychologic, social, and sport-specific issues. As well, we propose future directions in this field.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.490
Teacher spread0.366 · 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 designOther design
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

Citations74
Published2004
Admission routes1
Has abstractyes

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