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Record W2622636534 · doi:10.2217/cnc-2017-0006

Understanding blast-induced neurotrauma: how far have we come?

2017· review· en· W2622636534 on OpenAlexaff
Ibolja Černak

Bibliographic record

VenueConcussion · 2017
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExplosive materialBlast waveBlast injuryPsychologyMedicinePoison controlMedical emergencyHistoryEngineering

Abstract

fetched live from OpenAlex

Blast injuries, including blast-induced neurotrauma (BINT), are caused by blast waves generated during an explosion. Accordingly, their history coincides with that of explosives. Hence, it is intriguing that, after more than 1000 years of using explosives, our understanding of the pathological consequences of blast and body/brain interactions is extremely limited. Postconflict recovery mechanisms seemingly include the suppression of painful experiences, such as explosive injuries. Unfortunately, ignoring the knowledge generated by previous generations of scientists retards research progress, leading to superfluous and repetitive studies. This article summarizes clinical and experimental findings published about blast injuries and BINT following the wars of the 20th and 21th centuries. Moreover, it offers a personal view on potential factors interfering with the progress of BINT research working toward providing better diagnosis, treatment and rehabilitation for military personnel affected by blast exposure.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.696
GPT teacher head0.483
Teacher spread0.213 · 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 designNot applicable
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

Citations90
Published2017
Admission routes1
Has abstractyes

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