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Record W2055833323 · doi:10.1086/502350

Tuberculosis Prevention and Control in Long-Term–Care Facilities for Older Adults

2004· article· en· W2055833323 on OpenAlexaff
Lauri Thrupp, Suzanne Bradley, Philip W. Smith, Andrew E. Simor, Nelson M. Gantz, Kent Crossley, Mark Loeb, Larry J. Strausbaugh, Lindsay E. Nicolle

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2004
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcMaster UniversityHealth Sciences CentreUniversity of ManitobaSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineTuberculosisGuidelineTuberculosis preventionDiseaseInfection controlLong-term careHealth carePopulationDisease controlIntensive care medicineGerontologyEnvironmental healthNursingPathology

Abstract

fetched live from OpenAlex

In the United States, older adults comprise 22% of cases of tuberculous disease but only 12% of the population. Most cases of tuberculosis (TB) occur in community dwellers, but attack rates are highest among frail residents of long-term-care facilities. The detection and treatment of latent TB infection and TB disease can pose special challenges in older adults. Rapid recognition of possible disease, diagnosis, and implementation of airborne precautions are essential to prevent spread. It is the intent of this evidence-based guideline to assist healthcare providers in the prevention and control of TB, specifically in skilled nursing facilities for the elderly.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.322
Teacher spread0.308 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations41
Published2004
Admission routes1
Has abstractyes

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