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Record W1595038785 · doi:10.18433/j33591

An Overview Of Tuberculosis Chemotherapy – A Literature Review

2011· review· en· W1595038785 on OpenAlexafffundvenue
Susmita Sarkar, Mavanur R. Suresh

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2011
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of Alberta
FundersAlberta Glycomics Centre
KeywordsTuberculosisDrugMedicineRegimenIntensive care medicineDiseaseHuman immunodeficiency virus (HIV)PharmacologyImmunologySurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Tuberculosis (TB) is a major threat in global public health. The emergence of HIV and also multi drug resistant (MDR) and extremely drug resistant (XDR)-TB poses a vital challenge to the control of the disease. For the last 40 years, no new anti-TB drug has been discovered. This literature review provides a brief discussion of existing drugs and emerging drug targets, and also of the advantages of incorporating modern drug delivery systems and immune modulators in order to improve the existing treatment regimen in terms of better efficacy, reduced drug administration frequency, shortened period of treatment and reduced drug related toxicity. The investigation for new a drug target is essential in carrying on the fight against MDR and XDR-TB. However, owing to the enormous cost and time involved in new drug development, improvement of the existing treatment regimen is seen to be a valid alternative.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.007
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.332
GPT teacher head0.568
Teacher spread0.236 · 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 designSystematic review
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

Citations50
Published2011
Admission routes3
Has abstractyes

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