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Record W2725675172 · doi:10.1093/neuros/nyx344

The Berlin International Consensus Meeting on Concussion in Sport

2017· article· en· W2725675172 on OpenAlexaff
Gavin A Davis, Richard G. Ellenbogen, Julian E. Bailes, Robert C. Cantu, Karen M. Johnston, Geoffrey T. Manley, Shinji Nagahiro, Allen K. Sills, Charles H. Tator, Paul McCrory

Bibliographic record

VenueNeurosurgery · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsConcussionMedicinePresentation (obstetrics)Statement (logic)Poison controlMedical educationInjury preventionMedical emergencySurgeryLawPolitical science

Abstract

fetched live from OpenAlex

The Fifth International Conference on Concussion in Sport was held in Berlin in October 2016. A series of 12 questions and subquestions was developed and the expert panel members were required to perform a systematic review to answer each question. Following presentation at the Berlin meeting of the systematic review, poster abstracts and audience discussion, the summary Consensus Statement was produced. Further, a series of tools for the management of sport-related concussion was developed, including the Sport Concussion Assessment Tool Fifth edition (SCAT5), the Child SCAT5, and the Concussion Recognition Tool Fifth edition. This paper elaborates on this process, the outcomes, and explores the implications for neurosurgeons in the management of sport-related concussion.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.369
Teacher spread0.288 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations29
Published2017
Admission routes1
Has abstractyes

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