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Clinical Practice Guideline Recommendations in Pediatric Mild Traumatic Brain Injury: A Systematic Review

2023· review· en· W4390116172 on OpenAlexafffund
Lynne Moore, Anis Ben Abdeljelil, Pier‐Alexandre Tardif, Roger Zemek, Nick Reed, Keith Owen Yeates, Carolyn A. Emery, Isabelle Gagnon, Natalie Yanchar, Mélanie Berube, Jennifer Dawson, Simon Berthelot, Antonia Stang, Suzanne Beno, Émilie Beaulieu, Alexis F. Turgeon, Mélanie Labrosse, François Lauzier, Ian Pike, Alison Macpherson, Gabrielle Freire

Bibliographic record

VenueAnnals of Emergency Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity of British ColumbiaCentre hospitalier universitaire de QuébecYork UniversitySickKids FoundationUniversité de MontréalHospital for Sick ChildrenUniversity of TorontoMontreal Children's HospitalCentre Hospitalier Universitaire Sainte-JustineHotchkiss Brain InstituteToronto Rehabilitation InstituteAlberta Children's HospitalUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversité LavalInstitute for Clinical Evaluative SciencesMcGill University Health CentreHôpital de l'Enfant-Jésus
FundersCanadian Institutes of Health Research
KeywordsMedicineGuidelineTraumatic brain injuryClinical PracticeIntensive care medicineMEDLINESystematic reviewMedical emergencyFamily medicinePsychiatryPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.021
metaresearch head score (Gemma)0.113
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.113
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.787
GPT teacher head0.695
Teacher spread0.091 · 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 designSystematic review
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

Citations16
Published2023
Admission routes2
Has abstractno

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