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Record W4390932994 · doi:10.15690/vsp.v22i6.2700

Hereditary Amino Acid Metabolism Disorders and Urea Cycle Disorders: to Practicing Physician

2024· article· en· W4390932994 on OpenAlexaff
Nataliya V. Zhurkova, Nato D. Vashakmadze, Nataliya S. Sergienko, A. Dudina, Mariya S. Karaseva, Liliya R. Selimzyanova, Anna Yu. Rachkova, Yuliya Yu. Kotalevskaya, Andrey N. Surkov

Bibliographic record

VenueВопросы современной педиатрии · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsChildren’s Health Research Institute
Fundersnot available
KeywordsUrea cycleMedicineDiseaseAmino acid metabolismPediatricsHereditary DiseasesMetabolismPhysiologyInternal medicineAmino acidBiochemistryBiology

Abstract

fetched live from OpenAlex

Hereditary amino acid metabolism disorders (aminoacidopathies) are clinically and genetically heterogeneous group of hereditary metabolic diseases caused by enzymes deficiency involved in amino acid metabolism, that finally leads to progressive damage of central nervous system, liver, kidneys, and other organs and systems. Hereditary urea cycle disorders occur because of enzyme deficiency leading to impaired urea synthesis and hyperammoniemia in patients. The age of disease onset and clinical manifestations severity range from milder, intermittent forms to severe, manifesting in the first hours of life. Expanded neonatal screening (implemented in Russian Federation at 01.01.2023) allows to diagnose diseases from these groups in the first days of life, to prescribe timely pathogenetic therapy. Altogether it helps to prevent the development of disease severe complications. Raising awareness about hereditary aminoacidopathies and urea cycle disorders among pediatricians, neonatologists, neurologists, gastroenterologists, ophthalmologists is a topical issue of modern pediatrics.

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0240.011

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 head0.004
GPT teacher head0.242
Teacher spread0.238 · 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
Published2024
Admission routes1
Has abstractyes

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