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Record W2946416431 · doi:10.24908/pocus.v1i2.13254

Case Report: The use of gastric ultrasound to assess risk of pulmonary aspiration

2016· article· en· W2946416431 on OpenAlexvenueno aff
PGY- James Cheng

Bibliographic record

VenuePOCUS Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePulmonary aspirationAspiration pneumoniaAnesthesiologyPneumoniaComplicationSurgeryMechanical ventilationAnesthesiaStomachGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Pulmonary aspiration of gastric contents is a dreaded complication of general anesthesia, as it carries significant patient morbidity and mortality. Subsequent aspiration pneumonia can lead to prolonged mechanical ventilation, and a mortality rate of up to 5%. To minimize the risk of pulmonary aspiration, patients are required – as per the American Society of Anesthesiology’s “Practice Guidelines for Preoperative Fasting” – to fast prior to elective surgery in order to ensure that the stomach is empty prior to induction of general anesthesia.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0030.003
Scholarly communication0.0030.005
Open science0.0020.003
Research integrity0.0120.007
Insufficient payload (model declined to judge)0.0030.002

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 head0.074
GPT teacher head0.296
Teacher spread0.222 · 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 designCase report
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
Published2016
Admission routes1
Has abstractyes

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