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Record W1878399872 · doi:10.1016/j.tube.2015.05.017

Tuberculosis: A disease without boundaries

2015· review· en· W1878399872 on OpenAlexaff
Nicole Fogel

Bibliographic record

VenueTuberculosis · 2015
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsUniversity of VictoriaUniversity of Toronto
Fundersnot available
KeywordsTuberculosisDiseaseMedicineIntensive care medicineEpidemiologyMycobacterium tuberculosisPublic healthTransmission (telecommunications)ImmunologyPathology

Abstract

fetched live from OpenAlex

Tuberculosis (TB) is an airborne disease caused by Mycobacterium tuberculosis (MTB) that usually affects the lungs leading to severe coughing, fever, and chest pains. Although current research in the past four years has provided valuable insight into TB transmission, diagnosis, and treatment, much remains to be discovered to effectively decrease the incidence of and eventually eradicate TB. The disease still puts a strain on public health, being only second to HIV/AIDS in causing high mortality rates. This review will highlight the history of TB as well as provide an overview of the current literature on epidemiology, pathogenesis and the immune response, treatment, and control of TB. In this race to combat a disease that knows no boundaries, it is necessary to have a conceptual and clear understanding of TB overall with the hope of providing better treatment through novel and collaborative research and public health efforts.

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)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.087
GPT teacher head0.408
Teacher spread0.321 · 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

Citations326
Published2015
Admission routes1
Has abstractyes

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