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Record W7084747019 · doi:10.7910/dvn/hnk8gm

Replication Data for: Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

2025· dataset· en· W7084747019 on OpenAlexaff

Bibliographic record

VenueHarvard Dataverse · 2025
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsSouth asiaFecesReplication (statistics)Missing dataEnteric virusPathogenPolymerase chain reactionReal-time polymerase chain reaction

Abstract

fetched live from OpenAlex

This is a replication dataset for the manuscript titled: "Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children." This dataset contains the entire dataset of enteric biomarkers and quantitive polymerase chains reaction for enteric pathogens. Enteropathogen prevalence and fecal ED biomarkers (myeloperoxidase, calprotectin, α-1-antitrypsin) from children aged 2-23 months hospitalized at nine LMIC facilities (n=811) were compared to community children (n=248). Host and pathogen correlates of ED biomarkers were identified through crude and adjusted linear mixed effect models, and Cox-proportional hazard models assessed ED biomaker associations with inpatient and post-discharge mortality. The data collection CRFs and SOPs are available on our website at: https://chainnetwork.org/resources/.

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)0.004
metaresearch head score (Gemma)0.024
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0630.023

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 head0.221
Teacher spread0.213 · 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
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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