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Record W1848182291 · doi:10.3233/nre-2011-0708

Etiology of the post-concussion syndrome: Physiogenesis and psychogenesis revisited

2011· review· en· W1848182291 on OpenAlexafffund
Noah D. Silverberg, Grant L. Iverson

Bibliographic record

VenueNeurorehabilitation · 2011
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsGF Strong Rehabilitation CentreUniversity of British Columbia
FundersCanadian Institutes of Health ResearchWorld Health Organization
KeywordsEtiologyConcussionMedicinePost-concussion syndromePhysical medicine and rehabilitationPhysical therapyIntensive care medicineInjury preventionPoison controlPsychiatryMedical emergency

Abstract

fetched live from OpenAlex

In his seminal article, Physiogenesis and Psychogenesis in the 'Post-Concussional Syndrome,' Lishman (1988) proposed that neurobiological factors account for the development of the post-concussion syndrome and psychological factors become primarily responsible for maintaining it in the chronic phase. Over the 20 years that followed, researchers have advanced our understanding of the etiology of the post-concussion syndrome. Our review of this evidence suggests that neurobiological and psychological factors play a causal role in post-concussion symptoms from the outset, and thus, Lishman's causal model should be updated. If we can clinically identify individuals on a trajectory of poor recovery in the acute post-injury stage, then we can direct secondary prevention towards modifiable risk factors.

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)0.001
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.005
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.084
GPT teacher head0.379
Teacher spread0.295 · 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

Citations230
Published2011
Admission routes2
Has abstractyes

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