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Record W2135450160 · doi:10.3171/foc.2006.21.4.4

An overview of concussion consensus statements since 2000

2006· article· en· W2135450160 on OpenAlexfundno aff
Robert C. Cantu

Bibliographic record

VenueNeurosurgical FOCUS · 2006
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
FundersUniversity of North Carolina at Chapel HillMcGill University Health CentrePrinceton UniversityMcGill UniversityNorthwestern UniversityUniversity of PittsburghUniversity of Pennsylvania
KeywordsConcussionSports medicineSubject (documents)Athletic trainingConsensus conferenceMedical educationPsychologyMedicinePoison controlInjury preventionPhysical therapyLibrary scienceComputer scienceMedical emergency

Abstract

fetched live from OpenAlex

More refereed publications on sports-related concussion have appeared since 2000 than in all previous years combined. Three international consensus statements, documents from the National Athletic Trainers' Association (NATA) and the American College of Sports Medicine (ACSM), and entire issues of the Clinical Journal of Sport Medicine and the Journal of Athletic Training have been devoted to this subject. The object of this article is to critique the consensus statements and NATA and ACSM documents, pointing out areas of controversy.

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)0.093
metaresearch head score (Gemma)0.130
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 score0.093
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0930.130
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0330.039
Science and technology studies0.0030.001
Scholarly communication0.0060.006
Open science0.0040.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.125
GPT teacher head0.427
Teacher spread0.302 · 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

Citations60
Published2006
Admission routes1
Has abstractyes

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Same venueNeurosurgical FOCUSSame topicTraumatic Brain Injury ResearchFrench-language works237,207