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Record W3044117826 · doi:10.1007/s11682-020-00370-y

The ENIGMA sports injury working group:– an international collaboration to further our understanding of sport-related brain injury

2020· article· en· W3044117826 on OpenAlexafffund
Inga K. Koerte, Carrie Esopenko, Sidney R. Hinds, Martha E. Shenton, Elena M. Bonke, Jeffrey J. Bazarian, Kevin Bickart, Erin D. Bigler, Sylvain Bouix, Thomas A. Buckley, Meeryo Choe, Paul S. Echlin, Jessica Gill, Christopher C. Giza, Jasmeet P. Hayes, Cooper B. Hodges, Andrei Irimia, Paula Johnson, Kimbra Kenney, Harvey S. Levin, Alexander Lin, Hannah M. Lindsey, Michael L. Lipton, Jeffrey E. Max, Andrew R. Mayer, Timothy B. Meier, Kian Merchant‐Borna, Tricia L. Merkley, Brian D. Mills, Mary R. Newsome, Tara Porfido, Jaclyn A. Stephens, Maria Carmela Tartaglia, Ashley L. Ware, Ross Zafonte, Michael Zeineh, Paul M. Thompson, David F. Tate, Emily L. Dennis, Elisabeth A. Wilde, David Baron

Bibliographic record

VenueBrain Imaging and Behavior · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of CalgaryOntario Brain InstituteOccupational Cancer Research CentreUniversity of TorontoUniversity Health Network
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Biomedical Imaging and BioengineeringOffice of Naval ResearchNational Collegiate Athletic AssociationUniversity of California, Los AngelesOntario Trillium FoundationNational Institutes of HealthNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthCongressionally Directed Medical Research ProgramsAlzheimer's AssociationNational Institute on AgingEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. Department of Defense
KeywordsNeuroimagingNeuropsychologyTraumatic brain injuryGlobePsychologyAthletesData sharingComparabilityMedicineApplied psychologyPhysical medicine and rehabilitationNeurosciencePsychiatryPhysical therapyAlternative medicinePathologyCognition

Abstract

fetched live from OpenAlex

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor.

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)0.000
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 score0.214
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.068
GPT teacher head0.366
Teacher spread0.299 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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