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Record W2981683234 · doi:10.1016/j.apmr.2019.10.179

Management of Concussion and Mild Traumatic Brain Injury: A Synthesis of Practice Guidelines

2019· article· en· W2981683234 on OpenAlexaff
Noah D. Silverberg, Mary Alexis Iaccarino, William J. Panenka, Grant L. Iverson, Karen McCulloch, Kristen Dams-O’Connor, Nick Reed, Michael McCrea, Alison M. Cogan, Min Jeong P. Graf, Maria Kajankova, Gary McKinney, Christina Weyer Jamora

Bibliographic record

VenueArchives of Physical Medicine and Rehabilitation · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoHolland Bloorview Kids Rehabilitation HospitalGF Strong Rehabilitation CentreBC Mental Health & Substance Use ServicesUniversity of British Columbia
Fundersnot available
KeywordsConcussionTraumatic brain injurySpecialtyPsychological interventionAthletesMedicineClinical PracticeRehabilitationInjury preventionPoison controlPsychiatryPhysical therapyMedical emergency

Abstract

fetched live from OpenAlex

At least 3 million Americans sustain a mild traumatic brain injury (mTBI) each year, and 1 in 5 have symptoms that persist beyond 1 month. Standards of mTBI care have evolved rapidly, with numerous expert consensus statements and clinical practice guidelines published in the last 5 years. This Special Communication synthesizes recent expert consensus statements and evidenced-based clinical practice guidelines for civilians, athletes, military, and pediatric populations for clinicians practicing outside of specialty mTBI clinics, including primary care providers. The article offers guidance on key clinical decisions in mTBI care and highlights priority interventions that can be initiated in primary care to prevent chronicity.

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)0.028
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.079
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0110.010
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0050.004
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.406
Teacher spread0.358 · 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 designSystematic review
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

Citations349
Published2019
Admission routes1
Has abstractno

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