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Record W4235418585 · doi:10.1093/pch/pxx036

Eight-year-old girl with hepatomegaly

2017· article· en· W4235418585 on OpenAlexafffund
Becky Biqi Chen, Chitra Prasad, Joanna C. Walsh, Dhandapani Ashok

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsCanadian Institutes of Health ResearchChildren's Hospital of Western OntarioLondon Health Sciences CentreWestern University
FundersLondon Health Sciences Centre
KeywordsGirlPediatricsMedicinePsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

An 8-year-old girl was referred for abdominal pain and elevated liver transaminases. She was previously healthy and was not on any medications. There was no prior history of blood transfusions, toxin exposures or parenteral nutrition. Her parents were nonconsanguineous, and of French and Irish descent. Her family has no history of liver diseases but maternal and paternal grandparents have elevated cholesterol. Her weight was 25.5 kg (27th percentile), height 127 cm (21st percentile) and body mass index (BMI) was 15.8 kg/m2 (42nd percentile). On abdominal examination, both liver and spleen were enlarged. There was no scleral icterus or abnormal skin findings or xanthomatosis. Her liver enzymes revealed elevated transaminases. Total bilirubin was high at 32.7 (<17) µmol/L and direct bilirubin was 5 µmol/L. There was no coagulopathy. Abdominal ultrasound demonstrated her liver to be at near the 95th percentile while her spleen was also enlarged. Doppler study of liver vasculature was normal with no evidence of portal hypertension. Laboratory investigations are outlined in Table 1. Given the hepatomegaly, a lipid profile was performed, demonstrating elevated cholesterol of 6.11 (≤5.20) mmol/L and low HDL cholesterol of 0.83 (≥1.30) mmol/L. Further studies led to the diagnosis.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.008
GPT teacher head0.251
Teacher spread0.244 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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