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Record W2039754720 · doi:10.1080/16501960410023660

Systematic search and review procedures: results of the who collaborating centre task force on mild traumatic brain injury

2004· article· en· W2039754720 on OpenAlexaff
Linda Carroll, J. David Cassidy, Paul M. Peloso, Chantelle Garritty, Lori Giles‐Smith

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsycINFOTraumatic brain injuryCINAHLMEDLINESystematic reviewMedicinePhysical medicine and rehabilitationMandatePsychologyPsychiatryPsychological interventionPolitical science

Abstract

fetched live from OpenAlex

The WHO Collaborating Centre for Neurotrauma Task Force on Mild Traumatic Brain Injury performed a comprehensive search and critical review of the literature published between 1980 and 2002 to assemble the best evidence on the epidemiology, diagnosis, prognosis and treatment of mild traumatic brain injury. Our primary sources of literature were Medline, Cinahl, PsycINFO and Embase. Citations were screened for relevance to mild traumatic brain injury, using a priori criteria, and relevant studies were critically reviewed for scientific merit. We identified 38,806 citations, of which 671 studies were judged relevant to the mandate of the task force. These, plus 70 studies found by hand-searching reference lists and 2 original research reports performed as part of the task force mandate were subjected to critical reviews. After review, 313 (42%) were accepted on scientific merit and comprise our best-evidence synthesis. Ninety percent of the literature on mild traumatic brain injury was found in Medline and another 5% in PsycINFO.

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)0.078
metaresearch head score (Gemma)0.198
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.198
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0190.008
Bibliometrics0.0600.050
Science and technology studies0.0030.003
Scholarly communication0.0050.004
Open science0.0060.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0540.007

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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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.

Study designSystematic review
DomainMethods
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

Citations72
Published2004
Admission routes1
Has abstractyes

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