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Record W2995633007 · doi:10.1080/23320885.2019.1654388

High-pressure injection injury: a case report and systematic review

2019· article· en· W2995633007 on OpenAlexaff
Annica C. Eells, Matthew McRae, Rudolf F. Buntic, Daniel Boczar, Jeremie D. Oliver, María T. Huayllani, David J. Restrepo, Andrea Sisti, Antonio J. Forte

Bibliographic record

VenueCase Reports in Plastic Surgery and Hand Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicPneumothorax, Barotrauma, Emphysema
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDebridement (dental)MedicinePressure injurySurgerySystematic reviewHigh pressureIntensive care medicineMEDLINEEngineeringChemistry

Abstract

fetched live from OpenAlex

High-pressure delivery devices for paint and other substances can lead to severe injuries of the hand without immediate surgical debridement. We present a case of a high-pressure paint gun injury treated surgically with full resolution of function. A systematic review of the literature details outcomes of similar injuries.

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)0.002
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.265
Teacher spread0.247 · 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
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

Citations13
Published2019
Admission routes1
Has abstractyes

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