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Record W4413503519 · doi:10.1097/htr.0000000000001102

Progress in Concussion/Traumatic Brain Injury Science and Clinical Care Over the Last 40 Years

2025· article· en· W4413503519 on OpenAlexaff
Noah D. Silverberg, John J. Leddy

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British ColumbiaVancouver Coastal Health
Fundersnot available
KeywordsConcussionTraumatic brain injuryTerminologyHead injuryRehabilitationMedicineClinical PracticePhysical medicine and rehabilitationPsychologyPhysical therapyInjury preventionPoison controlPsychiatryMedical emergency

Abstract

fetched live from OpenAlex

This Special Communication summarizes how knowledge and clinical practice have evolved over the 40 years since the Journal of Head Trauma Rehabilitation 's topical issue (volume 1, issue 2) on "Minor Head Injury." We review important insights from this 1986 issue and highlight how research since has refined our understanding of concussion/traumatic brain injury pathophysiology, recovery, and long-term effects. We also discuss shifts in terminology and outline how assessment and rehabilitation approaches have developed over time. Finally, we call attention to areas of ongoing uncertainty and innovations that could help resolve them.

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)0.025
metaresearch head score (Gemma)0.041
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 score0.025
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.007
Science and technology studies0.0030.008
Scholarly communication0.0090.011
Open science0.0020.007
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0070.002

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 head0.044
GPT teacher head0.448
Teacher spread0.404 · 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
Published2025
Admission routes1
Has abstractyes

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