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Record W3214057547 · doi:10.36106/paripex/7200428

STUDY OF SPLENOMEGALY IN CHILDREN.

2021· article· en· W3214057547 on OpenAlexaff
Subhas Das, Chirag Shah, Rashmi Arora, Abhishek Mahna

Bibliographic record

VenuePARIPEX INDIAN JOURNAL OF RESEARCH · 2021
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsPsychologyMedicine

Abstract

fetched live from OpenAlex

Splenomegaly is common clinical finding in pediatric practice. Splenic enlargement occurs when the spleen is increased by cells or tissue components or by vascular engorgement. Various etiologies can cause splenomegaly. The spleen is rarely the primary site of a disease. Splenomegaly is classified according to the length palpable below the costal margin as mild: <3 cm, moderate: 4-7 cm & massive: >7 cm. Severe/massive splenomegaly doesn't commonly occur in first 5 years of age, occurs after 5 years of age. So, clinical examination of every child is important to diagnose splenomegaly at early stages. Only in the age group of 1 to 5 years females predominated as compared to males. In present study there is obvious male predominance as male: female ratio is 1.8:1. This difference could be due to more priority to male child to seeking medical care with such chronic illness.Present study also suggested that severe/massive splenomegaly doesn't commonly occur in first 5 years of age, occurs after 5 years of age. So, clinical examination of every child is important to diagnose splenomegaly at early stages.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.437
Teacher spread0.352 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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