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Record W4398511629 · doi:10.7910/dvn/942and

Replication Data for: Triage and management of sepsis in children using the point-of care Pediatric Rapid Sepsis Trigger (PRST) tool

2023· dataset· en· W4398511629 on OpenAlexaff
Joyce Kigo, Stephen Kamau, Samuel Akech, Dustin Dunsmuir, Yashodani Pillay, J. Mark Ansermino, Mary Ouma, David Kimutai, Ismael Mohamed, Mary Chege, Lydia Thuranira

Bibliographic record

VenueHarvard Dataverse · 2023
Typedataset
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTriageSepsisReplication (statistics)MedicinePoint of careIntensive care medicineEmergency medicineInternal medicineVirologyPathology

Abstract

fetched live from OpenAlex

This is a replication dataset for the manuscript titled "Triage and management of sepsis in children using the point-of care pediatric Rapid Sepsis Trigger(PRST) tool." The data was collected as part of PRST study phase 1 which was carried out in Mbagathi County Hospital (Hospital 1)and Kiambu teaching and Referral hospital(Hospital 2) between February 2021 to October 2021 which involved enrolling patients arriving at the outpatient department and collecting patient characteristics . Study standard operating procedure, data dictionary, data collection software and code can be found on Paediatric Sepsis CoLab Dataverse (Mawji A. Smart Triage Jinja Standard Operating Protocols. V1 ed: Borealis; 2021.)

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)0.007
metaresearch head score (Gemma)0.062
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 score0.106
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1060.048

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 head0.085
GPT teacher head0.350
Teacher spread0.265 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHarvard Dataverse→Same topicSepsis Diagnosis and Treatment→French-language works237,207→