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Record W2427470371 · doi:10.1093/trstmh/trv039

Development of Leishmania vaccines in the era of visceral leishmaniasis elimination

2015· article· en· W2427470371 on OpenAlexafffund
Christian Engwerda, Gregory J. Matlashewski

Bibliographic record

VenueTransactions of the Royal Society of Tropical Medicine and Hygiene · 2015
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsVisceral leishmaniasisLeishmaniasisIndian subcontinentLeishmaniaImmunologyVaccinationMedicineVirologyComputer scienceHistory

Abstract

fetched live from OpenAlex

A visceral leishmaniasis (VL) elimination target set for the Indian subcontinent in 2005 is being met in many endemic areas without a vaccine. This begs a question: is a VL vaccine needed if elimination targets can be met with current control programs? Here, we argue that a vaccine will be critical if the success of recent VL control efforts are to be sustained. However, not only do we require a safe and effective vaccine, but we also need to know how this should be used for maximum impact. In particular, identifying appropriate target populations to vaccinate will be crucial.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.309
Teacher spread0.263 · 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.

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

Citations33
Published2015
Admission routes2
Has abstractyes

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