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Record W4205896558 · doi:10.17863/cam.71875

Latent Tuberculosis: Two Centuries of Confusion.

2021· article· en· W4205896558 on OpenAlexaff
Marcel A. Behr, Eva Kaufmann, Jacalyn Duffin, Paul H. Edelstein, Lalita Ramakrishnan

Bibliographic record

VenueApollo (University of Cambridge) · 2021
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsQueen's UniversityMcGill UniversityChristie (Canada)
FundersWellcome Trust
KeywordsMedicineConfusionTuberculosisMEDLINEPsychoanalysisPathology

Abstract

fetched live from OpenAlex

The term latent tuberculosis (TB) was coined two centuries ago to describe post-mortem tuberculous pathology in the absence of ante-mortem tuberculosis manifestations. However, the meaning of the term has changed with each passing century, engendering confusion. In the early 20th century, with the advent of microbiological assays for live tubercle bacteria, latent TB switched from the host to refer to the bacteria from post-mortem tissues of nontuberculous hosts. Then in the late 20th century, the definition of latent TB infection returned to the host, this time referring to those with immunoreactivity to Mycobacterium tuberculosis antigens. Based on this new definition, latent TB infection is unique among bacterial infectious diseases, in that supportive evidence of the infection state is sought by the absence of the causative bacterium and its clinical manifestations. The use of indirect bedside and laboratory tests to denote infection creates clinical and research confusion, as the tests for immunoreactivity suffer from recognized limitations in sensitivity and specificity. We propose that the concept of latent TB infection be separated from that of tuberculous immunoreactivity in the interest of correct diagnosis and focused treatment, correct formulation and interpretation of research questions and better allocation of programmatic resources for TB elimination. To this end, we suggest new terminology to course-correct our thinking about tuberculous infection (TBI) which is subdivided into tuberculous infection-no disease (TBInd) and the long-accepted term for the disease, tuberculosis (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 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)0.013
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0040.049
Scholarly communication0.0090.014
Open science0.0020.008
Research integrity0.0100.021
Insufficient payload (model declined to judge)0.0030.002

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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 designTheoretical or conceptual
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

Citations65
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueApollo (University of Cambridge)Same topicTuberculosis Research and EpidemiologyFrench-language works237,207