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Gastric Ultrasound in the Third Trimester of Pregnancy: A Randomized Controlled Trial to Develop a Predictive Model of Volume Assessment

2018· article· en· W2901487665 on OpenAlexaff
Cristián Arzola, Anahi Perlas, Naveed Siddiqui, K. Downey, X.Y. Ye, J.C.A. Carvalho

Bibliographic record

VenueObstetric Anesthesia Digest · 2018
Typearticle
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineStomachGastric ContentAntrumGastric fluidUltrasoundIngestionGastric antrumPregnancyVolume (thermodynamics)Second trimesterObstetricsInternal medicineRadiologyGestation

Abstract

fetched live from OpenAlex

( Anaesthesia . 2018;73:295–303) Bedside gastric ultrasound is used in diverse patient groups for the assessment of gastric content and volume. Using qualitative assessment, a distinction can be made between an empty stomach and one containing solid/thick fluid contents or clear fluids. In addition, quantitative assessment of gastric volume can be estimated using the cross-sectional area of the gastric antrum when clear fluid contents are present in the stomach. Small volumes ≤1.5 mL/kg 1 are consistent with baseline gastric secretions, whereas higher volumes suggest patient ingestion that may increase aspiration risk. The primary objective of this study was to evaluate the relationship between gastric antral cross-sectional area as measured by ultrasound and the volume of clear fluids ingested by pregnant women.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
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 head0.021
GPT teacher head0.282
Teacher spread0.262 · 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 designRandomized trial
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

Citations4
Published2018
Admission routes1
Has abstractyes

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