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Monitoring LFCN damage during scoliosis surgery

2015· article· en· W52621466 on OpenAlexaffabout
Negar Behzadi Fard, Aleksandra Krajacic, François D. Roy, Sarah Southon, Kajsa Duke

Bibliographic record

VenueScoliosis · 2015
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsAlberta Health ServicesUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineScoliosisSurgerySomatosensory evoked potentialAnterior superior iliac spineCarpal tunnel releaseThighSpinal surgeryAnesthesia

Abstract

fetched live from OpenAlex

Material and methods Three pressure mats (FSA, Vista Medical, Winnipeg) were placed on the Jackson frame before positioning the patient. Data was continuously recorded during surgery and the average and maximum pressures on the chest, left and right hip/thigh region was calculated (Figure 1). The LFCN SSEP was tested by stimulating the anterolateral thigh and recording the evoked potentials over the somatosensory cortex. An increase in latency and/or decrease in SSEP amplitude may be indicative of LFCN dysfunction. At present, data on five patients was recorded. Post-operative evaluation of the front of the iliac crests is performed and the appearance of redness (Figure 2), blisters or pressure sores are documented. Additionally, after surgery, the patients were asked if they feel any numbness on the front of the thighs and manual tests for sensation were performed every day until discharge.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.067
GPT teacher head0.307
Teacher spread0.240 · 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 designObservational
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

Citations1
Published2015
Admission routes2
Has abstractyes

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