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Record W2987755711 · doi:10.14309/ajg.0000000000000459

Major Complications of Pediatric Percutaneous Liver Biopsy Do Not Differ Among Physicians With Different Degrees of Training

2019· article· en· W2987755711 on OpenAlexaff
Natascha Silva Sandy, Gabriel Hessel, Maria Angela Bellomo‐Brandão

Bibliographic record

VenueThe American Journal of Gastroenterology · 2019
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineBiopsyPercutaneousLiver biopsyGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The objective was to compare safety of pediatric percutaneous liver biopsy (PLB) performed by fellows or staff physicians. METHODS: Outcomes of 212 PLB completed by first-year pediatric gastroenterology fellows or by staff physicians over 8 years were analyzed and compared. RESULTS: Approximately 81.5% of the biopsies were completed by trainees. No significant differences were found between groups (fellows vs staff) regarding number of punctures (median of 1.7 for both), nonrepresentative biopsies (4.2% vs 2.6%), and hemoglobin drop (median of 0.7 vs 0.5 g/L). DISCUSSION: Complications of pediatric PLB are uncommon and did not differ among physicians with different training levels.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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.

Study designObservational
DomainMethods
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

Citations10
Published2019
Admission routes1
Has abstractyes

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