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Record W2264487920 · doi:10.1017/cbo9780511734847.013

Hypotension following spinal anesthesia

2011· book-chapter· en· W2264487920 on OpenAlexaff
C Delbridge, I. McConachie

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook-chapter
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineNeuraxial blockadeUltrasoundAnesthesiaDiagnostic ultrasoundGold standard (test)BlockadeSpinal anesthesiaRadiologyInternal medicine

Abstract

fetched live from OpenAlex

This chapter presents evidence supporting the use of ultrasound to take the epidural catheterization and spinal injections away from being blind techniques, therefore aiming to help reduce the incidence of the potentially serious complications resulting from Central neuraxial blockade (CNB). CNB remains the gold standard technique of providing both analgesia and anesthesia in the obstetric population, a fact which is unlikely to change in the near future. Creating an ultrasound image is done in three steps: producing a sound wave, receiving the echoes and interpreting those echoes. Most diagnostic ultrasound transducers use artificial polycrystalline ferroelectric materials such as lead zirconate titanate. There is very little published data regarding the use of ultrasound for real-time visualization of epidural puncture for neuraxial blockade. Overall, the use of ultrasound in all aspects of regional anesthesia allows continual development and improvement of current techniques.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.034
GPT teacher head0.209
Teacher spread0.175 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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