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Record W4240080242 · doi:10.1002/9781444345100.ch75

Mangled Extremity

2011· other· en· W4240080242 on OpenAlexaff
Ted Tufescu

Bibliographic record

VenueEvidence-Based Orthopedics · 2011
Typeother
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The mangled extremity is a severe injury involving at least three of four tissue groups, which may lead to amputation. Gustilo IIIB and C fractures have significant amputation rates and likely represent mangled extremities. It is unclear when the extremity can be salvaged or requires amputation. Factors that influence this decision are reviewed in this chapter. Duration of hospitalization and rehabilitation are equal for salvage and amputation. The cost of amputation is higher only when life-time prosthesis related costs are considered. Certain patient characteristics predict poor outcome and difficulty with return to work, but do not discriminate between salvage and amputation. Scoring systems created to objectively guide treatment do predict salvage accurately; however they do not predict amputation or function. The presence of an insensate foot also does not necessitate amputation, as half the patients regain normal sensation. There is no difference in outcome with salvage or amputation. Both groups are disabled and only half return to work. Salvage patients, however, have a higher risk of complications.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.002

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 head0.063
GPT teacher head0.302
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2011
Admission routes1
Has abstractyes

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