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Record W4411374577 · doi:10.1128/mra.01317-24

Hybrid reference genome assemblies for <i>Leishmania (Viannia) braziliensis</i> , a primary agent of mucocutaneous leishmaniasis

2025· article· en· W4411374577 on OpenAlexaff
James A. Cotton, Frederik Van den Broeck, Peter J. Myler, Natalia S. Akopyants, Matthew Berriman, Stephen M. Beverley

Bibliographic record

VenueMicrobiology Resource Announcements · 2025
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthWellcome Trust
KeywordsMucocutaneous zoneLeishmania braziliensisLeishmaniasisLeishmaniaBiologyInfectivityGenomeVirologyCutaneous leishmaniasisImmunologyMedicineGeneParasite hostingGeneticsDiseasePathologyVirusComputer science

Abstract

fetched live from OpenAlex

ABSTRACT We report high-quality long-read genome assemblies and annotations for two widely studied reference strains of Leishmania (Viannia) braziliensis , a primary agent of cutaneous and mucocutaneous leishmaniasis. These genomes should facilitate studies of animal infectivity and pathogenesis of cutaneous and severe mucocutaneous leishmaniasis.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.295
Teacher spread0.270 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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