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Record W4401565428 · doi:10.1101/2024.08.13.24311555

Documented transboundary transmission of mpox between the Central African Republic and the Democratic Republic of the Congo

2024· preprint· en· W4401565428 on OpenAlexaff
Emmanuel Hasivirwe Vakaniaki, Eddy Kinganda-Lusamaki, Sydney Merritt, Emile Malembi, Lygie Lunyanga, Sylvie Linsuke, Megan Halbrook, Ernest Kalthan, Elisabeth Pukuta, Adrienne Amuri-Aziza, Jean-Claude Makangara-Cigolo, Raphael Lumembe, Gabriel Kabamba, Yvon Anta, Pierrot Bolunza, Innocent Kanda, Raoul Nganzobo, Thierry Kalonji-Mukendi, Justus Nsio, Patricia Matoka, Dieudonné Mwamba, Christian Ngandu, Souradet Y. Shaw, Robert Shongo, Joule Madinga, Yap Boum, Laurens Liesenborghs, Éric Delaporte, Ahidjo Ayouba, Nicola Low, Steve Ahuka Mundeke, Lisa E. Hensley, Jean‐Jacques Muyembe Tamfum, Emmanuel Nakouné, Martine Peeters, Nicole A. Hoff, Jason Kindrachuk, Anne W. Rimoin, Placide Mbala‐Kingebeni

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDemocracyTransmission (telecommunications)The RepublicGeographyPolitical scienceSubcladeEnvironmental protectionBiologyCladePoliticsGeneGeneticsLawPhylogenetics

Abstract

fetched live from OpenAlex

ABSTRACT Four confirmed mpox cases in South Ubangi province, Democratic Republic of the Congo, were linked to documented transboundary transmission from Central African Republic. Viral genome sequencing shows that the MPXV sequences belong to subclade Ia. This demonstrates the borderless nature of mpox and highlights the need for vigilant regional surveillance.

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 score0.014
Threshold uncertainty score0.029

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.262
Teacher spread0.246 · 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
Published2024
Admission routes1
Has abstractyes

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