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Record W1973546046 · doi:10.3357/asem.2181.2008

Regional Anesthesia for the Management of Limb Injuries in Space

2008· review· en· W1973546046 on OpenAlexafffund
Gregory L. Silverman, Colin J. L. McCartney

Bibliographic record

VenueAviation Space and Environmental Medicine · 2008
Typereview
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of Toronto
FundersCanadian Space Agency
KeywordsSpaceflightHuman spaceflightAeronauticsSpace ShuttleLow earth orbitMedicineSpace explorationComputer scienceEngineeringAerospace engineeringSatellite

Abstract

fetched live from OpenAlex

Traumatic injuries continue to present a threat to the success of current and future spaceflight missions. The magnitude of this threat will grow as the frequency of extravehicular activities is increased and missions venture beyond low Earth orbit and further away from terrestrial medical support. The capability to render definitive treatment to crewmembers who suffer a serious traumatic injury while in space is relatively limited at present. While some research has focused on the development of specific surgical techniques for the microgravity environment, little attention has been given to how one might practically provide anesthetic care for injured crewmembers expected to undergo these procedures. While many logistical and practical obstacles exist to the provision of general anesthesia in microgravity, regional anesthesia could be used to overcome many of these problems. A regional anesthetic capability for spaceflight missions could be developed with minimal modifications to existing terrestrial techniques and would provide the ability to manage a wide range of potential injuries while in orbit. The capability to provide reliable regional anesthesia could be further augmented and improved using a range of imaging technologies currently in development; it is expected that these devices would have a range of terrestrial applications, including the ability to provide immediate, safe, and reliable anesthetic care to patients in remote locations, or under austere conditions such as the combat environment.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.306
Teacher spread0.275 · 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 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

Citations23
Published2008
Admission routes2
Has abstractyes

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