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Record W2918999460 · doi:10.1097/htr.0000000000000455

Strengthening the Evidence Base: Recommendations for Future Research Identified Through the Development of CDC's Pediatric Mild TBI Guideline

2019· article· en· W2918999460 on OpenAlexaff
Stacy J. Suskauer, Keith Owen Yeates, Kelly Sarmiento, Edward C. Benzel, Matthew J. Breiding, Catherine Broomand, Juliet Haarbauer‐Krupa, Michael S. Turner, Barbara Weissman, Angela Lumba‐Brown

Bibliographic record

VenueJournal of Head Trauma Rehabilitation · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsDefence Research and Development Canada
FundersNational Institutes of Health
KeywordsGuidelineMedicinePsychologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The recently published Centers for Disease Control and Prevention evidence-based guideline on pediatric mild traumatic brain injury (mTBI) was developed following an extensive review of the scientific literature. Through this review, experts identified limitations in existing pediatric mTBI research related to study setting and generalizability, mechanism of injury and age of cohorts studied, choice of control groups, confounding, measurement issues, reporting of results, and specific study design considerations. This report summarizes those limitations and provides a framework for optimizing the future quality of research conduct and reporting. RESULTS: Specific recommendations are provided related to diagnostic accuracy, population screening, prognostic accuracy, and therapeutic interventions. CONCLUSION: Incorporation of the recommended approaches will increase the yield of eligible research for inclusion in future systematic reviews and guidelines for pediatric mTBI.

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)0.282
metaresearch head score (Gemma)0.508
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score0.885

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2820.508
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0120.019
Bibliometrics0.0180.013
Science and technology studies0.0040.004
Scholarly communication0.0170.017
Open science0.0130.010
Research integrity0.0220.019
Insufficient payload (model declined to judge)0.0100.004

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 head0.249
GPT teacher head0.487
Teacher spread0.238 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreMethods

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

Citations22
Published2019
Admission routes1
Has abstractyes

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