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Record W2791461373 · doi:10.2217/cnc-2017-0015

Sex & gender considerations in concussion research

2018· review· en· W2791461373 on OpenAlexaff
Tatyana Mollayeva, Graziella El-Khechen-Richandi, Angela Colantonio

Bibliographic record

VenueConcussion · 2018
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsConcussionMedicineBiological sexPsychologyInjury preventionPsychiatryPoison controlMedical emergencyDevelopmental psychology

Abstract

fetched live from OpenAlex

The study of concussion, a common form of mild traumatic brain injury, has received increased notice over the last decade. Recently, more researchers have been addressing the historic paucity of attention over sex and gender influences on recovery outcomes after concussion. This development has led to exciting progress in our understanding of concussion incidence and outcomes. In this review, we will report on new findings from varying studies on sex differences in the epidemiology of concussion and clinical manifestations of mild traumatic brain injury/concussion, further discussing some key issues related to the integration of sex and gender in concussion research in a broad range of contexts, with recommendations to guide future research, along with sex- and gender-sensitive policy considerations.

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)0.004
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.696
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.005

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 head0.561
GPT teacher head0.543
Teacher spread0.019 · 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; both teacher heads agree on what is shown here.

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

Citations100
Published2018
Admission routes1
Has abstractyes

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