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Record W2608875080 · doi:10.1136/bjsports-2017-097569

The Berlin 2016 process: a summary of methodology for the 5th International Consensus Conference on Concussion in Sport

2017· article· en· W2608875080 on OpenAlexaff
Willem Meeuwisse, Kathryn Schneider, Jiří Dvořák, Onutobor Omu, Caroline F. Finch, Alix Hayden, Paul McCrory

Bibliographic record

VenueBritish Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsConcussionDelphi methodConsensus conferenceDelphiMedical educationMedicinePsychologyPoison controlInjury preventionComputer scienceMedical emergencyArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this paper is to summarise the methodology for the 5th International Consensus Conference on Concussion in Sport. The 18 months of preparation included engagement of a scientific committee, an expert panel of 33 individuals in the field of concussion and a modified Delphi technique to determine the primary questions to be answered. The methodology also involved the writing of 12 systematic reviews to inform the consensus conference and submission and review of scientific abstracts. The meeting itself followed a 2-day open format, a 1-day closed expert panel meeting and two additional half day meetings to develop the Concussion Recognition Tool 5 (Pocket CRT5), Sport Concussion Assessment Tool 5 (SCAT5) and Child SCAT5.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.163
GPT teacher head0.441
Teacher spread0.278 · 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

Citations84
Published2017
Admission routes1
Has abstractyes

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