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Record W2107864482 · doi:10.1586/14787210.5.1.61

International Standards for Tuberculosis Care: revisiting the cornerstones of tuberculosis care and control

2007· review· en· W2107864482 on OpenAlexaff
Elizabeth Fair, Philip C. Hopewell, Madhukar Pai

Bibliographic record

VenueExpert Review of Anti-infective Therapy · 2007
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University
Fundersnot available
KeywordsTuberculosisTuberculosis controlMedicineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Tuberculosis (TB) remains an enormous global health problem. There are 8-9 million new cases and 2 million deaths from TB annually. Despite the overwhelming burden of disease, the basic principles of care for persons with, or suspected of having, TB are the same worldwide: a diagnosis should be established promptly and accurately, standardized treatment regimens of proven efficacy should be used together with appropriate treatment support and supervision, the response to treatment should be monitored, and the essential public health responsibilities must be carried out. As an approach to improving the care of patients with TB, an evidence-based document, the International Standards for Tuberculosis Care (ISTC) was developed and has been endorsed by more than 30 international and national agencies. This special report introduces the ISTC and discusses the fact that accurate diagnosis and effective treatment are not only essential for good patient care, they are the key elements in the public health response to TB and are the cornerstone of TB control. With the recent emergence of extensively drug-resistant TB, there is an urgent need to ensure globally that standards of TB care are based on rigorous scientific findings, are clear and well understood, and are accessible to and applied by all types of healthcare providers in all corners of the world.

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)0.043
metaresearch head score (Gemma)0.049
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: Review · Consensus signal: Review
Teacher disagreement score0.043
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.049
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0080.011
Science and technology studies0.0010.005
Scholarly communication0.0050.006
Open science0.0070.003
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0040.004

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 head0.044
GPT teacher head0.443
Teacher spread0.399 · 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
GenreReview

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

Citations27
Published2007
Admission routes1
Has abstractyes

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