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Record W4401420831 · doi:10.3201/eid3009.231595

Emerging <i>Leishmania donovani</i> Lineages Associated with Cutaneous Leishmaniasis, Himachal Pradesh, India, 2023

2024· article· en· W4401420831 on OpenAlexfundno aff
Patrick Lypaczewski, Yogesh Chauhan, Kayla Paulini, Lovlesh Thakur, Shailja Chauhan, Ezrah Isaac Roy, Greg Matlashewski, Manju Jain

Bibliographic record

VenueEmerging infectious diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchInternational Centre for Genetic Engineering and BiotechnologyIndian Council of Medical Research
KeywordsLeishmania donovaniEndemic diseasesLeishmaniasisCutaneous leishmaniasisLeishmaniaNeglected tropical diseasesBiologyMedicineVirologyVeterinary medicineTraditional medicineEnvironmental healthGeographyVisceral leishmaniasisImmunologyPublic healthPathologyParasite hosting

Abstract

fetched live from OpenAlex

The clinical manifestation of leishmaniasis has historically been determined by the Leishmania species involved. However, recent emergence of novel Leishmania lineages has caused atypical pathologies. We isolated and characterized 2 new Leishmania donovani parasites causing cutaneous leishmaniasis in Himachal Pradesh, India.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.286
Teacher spread0.274 · 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 teacher head, not a consensus.

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

Citations10
Published2024
Admission routes1
Has abstractyes

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