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Record W7099137532

Recommended Citation

2015· article· en· W7099137532 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakIncidence (geometry)Health careAcute careWork (physics)Infectious disease (medical specialty)Exploratory researchDisease
DOInot available

Abstract

fetched live from OpenAlex

outbreaks and increased complexity of care. International Nursing Review Aim: This study examined the effects of healthcare-associated infectious disease outbreaks on nurses ’ work in a large acute care hospital in Ontario, Canada. Background: The incidence of healthcare-associated infections has increased. Previous research focuses on epidemiology, healthcare systems, and the economic burden of outbreaks. Few published studies focus on the impact of outbreaks on nurses ’ work in acute care facilities. Introduction: Since the severe acute respiratory syndrome epidemic in 2003, combating infectious diseases has become a key issue. Hospitals have implemented measures related to healthcare-associated infections. However, nurses experience challenges in preventing, controlling, and contending with outbreaks. Methods: A retrospective exploratory case study approach was used. Data were collected over a 4-month period in 2012. The incidence rates of site-specific HAIs were analysed, and individual interviews were held

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.187
GPT teacher head0.398
Teacher spread0.211 · 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 designNot applicable
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

Citations0
Published2015
Admission routes1
Has abstractyes

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