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Record W2789646173 · doi:10.1371/journal.pmed.1002544

Time for high-burden countries to lead the tuberculosis research agenda

2018· editorial· en· W2789646173 on OpenAlexaff
Madhukar Pai

Bibliographic record

VenuePLoS Medicine · 2018
Typeeditorial
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill University
Fundersnot available
KeywordsTuberculosisExtensively drug-resistant tuberculosisGlobal healthLow and middle income countriesMedicineEnvironmental healthEconomic growthMEDLINEPublic healthDeveloping countryDevelopment economicsPolitical scienceMycobacterium tuberculosisEconomicsPathology

Abstract

fetched live from OpenAlex

At long last, tuberculosis (TB) is getting the political attention that it deserves, being the leading infectious killer of humans today. In 2016, there were 10.4 million estimated new TB cases, with over 1.7 million deaths [1]. The G20 declaration of July 2017 included TB in the context of the need to respond to the antimicrobial resistance threat, following the group's meeting in Hamburg, Germany In November 2017, for the first time, a WHO Global Ministerial Conference on TB was held in Moscow, Russia, culminating in the Moscow Declaration to End TB [3]. This year, in September, the United Nations General Assembly (UNGA) will hold the first-ever high-level meeting on the fight against TB

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)0.006
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.003

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 head0.061
GPT teacher head0.397
Teacher spread0.336 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations16
Published2018
Admission routes1
Has abstractyes

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