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Record W4385812434 · doi:10.12688/gatesopenres.14396.2

Adult malaria mortality during 2019 at Bo Government Hospital, Sierra Leone

2023· preprint· en· W4385812434 on OpenAlexaff
Satta Sylvia Theresa Kumba Kpagoi, Ashley Aimone, Rashid Ansumana, Ibrahim Swaray, Hellen Gelband, John W. Eikelboom, Prabhat Jha, Isaac I. Bogoch

Bibliographic record

VenueGates Open Research · 2023
Typepreprint
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversity of TorontoMcMaster UniversityCentre for Global Health Research
FundersBill and Melinda Gates Foundation
KeywordsSierra leoneMalariaGovernment (linguistics)MedicineEthnologyHistoryImmunology

Abstract

fetched live from OpenAlex

<ns4:p> It is uncertain whether malaria is an important cause of death among adults in endemic areas. We performed a chart review of adults admitted to Bo Government Hospital during 2019. Of 893 admissions, 149 (59% female, mean age 58.5 years) had a laboratory diagnosis of malaria and 22 (14.8%) died. Mortality was significantly higher among patients with severe malaria compared with those who had non-severe malaria (6/20 [30%] versus 16/129 [12.4%], <ns4:italic>p</ns4:italic> =0.031). Our results suggest that malaria is a common cause of death in hospitalized Sierra Leonian adults. </ns4:p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.020
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.004

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 head0.098
GPT teacher head0.409
Teacher spread0.311 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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