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Record W4417458162 · doi:10.55460/8oqn-uu7u

"Ruck-Truck-House-Plane" Plan Application for the Management of Combat-Related Wound Infections and Prevention of Multidrug-Resistant Organism Spread in Prolonged Field Care Scenarios

2025· article· en· W4417458162 on OpenAlexaff
Pierre Pasquier, Philippe Laitselart, Mathieu David, Tristan Alie, Florent Josse, Sean Keenan

Bibliographic record

VenueJournal of Special Operations Medicine · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMontfort HospitalCanadian Armed Forces
Fundersnot available
KeywordsWound careInfection controlAntimicrobial stewardshipStewardship (theology)OrganismRisk managementHealth care

Abstract

fetched live from OpenAlex

Wound infections represent an increasing risk in combat trauma, especially in prolonged casualty care conditions char-acterized by evacuation delays and resource scarcity. This risk is compounded by multidrug-resistant organisms, which are difficult to detect and treat in austere settings. This article introduces a "Ruck-Truck-House-Plane" model for infection control and wound management in prolonged casualty care (Role 1) and prolonged care (beyond Role 1) environments. This original approach includes practical procedures and de-cision-making from point of injury to tertiary care transfer. It emphasizes early decontamination, phased surgical care, re-mote microbial diagnostics, and antimicrobial stewardship to reduce morbidity and mortality in modern warfare.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.367
Teacher spread0.346 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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