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Record W2898849466 · doi:10.3390/tropicalmed3040115

Tuberculosis Elimination in the Asia-Pacific Region and the WHO Ethics Guidance

2018· article· en· W2898849466 on OpenAlexaff
Justin T. Denholm, Diego S. Silva, Erlina Burhan, Richard E. Chaisson

Bibliographic record

VenueTropical Medicine and Infectious Disease · 2018
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsSimon Fraser University
FundersNational Institute of Allergy and Infectious Diseases
KeywordsTuberculosisAsia pacificContext (archaeology)Public healthPolitical scienceWork (physics)Public relationsMedicineEconomic growthGeographySociologyPathologyEngineeringEthnologyEconomicsArchaeology

Abstract

fetched live from OpenAlex

The World Health Organization has produced ethical guidance on implementation of the End TB strategy, which must be considered in local context. The Asia-Pacific Region has important distinctive characteristics relevant to tuberculosis, and engagement with the ethical implications raised is essential. This paper highlights key ethical considerations for the tuberculosis elimination agenda in the Asia-Pacific Regions and suggests that further programmatic work is required to ensure such challenges are addressed in clinical and public health programs.

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)0.069
metaresearch head score (Gemma)0.065
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: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.022
Scholarly communication0.0110.006
Open science0.0020.007
Research integrity0.0110.024
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.354
Teacher spread0.312 · 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
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
Published2018
Admission routes1
Has abstractyes

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