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Record W2123375245 · doi:10.1086/656411

Infectious Diseases in the Nursing Home Setting: Challenges and Opportunities for Clinical Investigation

2010· review· en· W2123375245 on OpenAlexaboutno aff
Manisha Juthani‐Mehta, Vincent Quagliarello

Bibliographic record

VenueClinical Infectious Diseases · 2010
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute on Aging
KeywordsDementiaNursing homesMedicineGerontologyNursingDiseasePopulation ageingImmunosenescenceGerontological nursingPublic healthInfectious disease (medical specialty)GeriatricsQuarter (Canadian coin)PopulationFamily medicineEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

The global population is aging. With the high prevalence of dementia and functional decline in older Americans, many aging adults with disabilities reside in nursing homes in their final stage of life. Immunosenescence, multiple comorbid diseases, and grouped quarter living all coalesce in nursing home residents to increase the risk for infectious disease. The unique issues involved with diagnosis, prognosis, and management of infectious diseases in nursing home residents make research based in the nursing home setting both necessary and exciting for the physician investigator. This review discusses the opportunities and challenges involved with research of the evolving public health problem of infections among nursing home residents.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.003
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 head0.390
GPT teacher head0.541
Teacher spread0.151 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations78
Published2010
Admission routes1
Has abstractyes

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