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Bibliometrics analysis of subsyndromal delirium

2019· article· en· W3031212692 on OpenAlexaboutno aff
Jiawei Qian

Bibliographic record

Venue˜The œJournal of practical nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDeliriumCochrane LibraryObservational studyMedicineBibliometricsIncidence (geometry)MEDLINEPsychologyAlternative medicineIntensive care medicinePolitical scienceLibrary scienceInternal medicinePathology

Abstract

fetched live from OpenAlex

Objective To analyze the current status of subsyndromal delirium in recent years, to provide information for the study of subsyndromal delirium in China. Methods Bibliometric methods were used to analyze the subsyndromal delirium related literature published in Pubmed, Embase, Web of Science, EBSCO, Cochrane Library, Wanfang and CNKI. Results A total of 68 articles were included in 48 journals, Literature was mainly published in Canada and the United States, including observational research, systematic reviews, and experimental research. The main subjects are elderly patients from ICU, Nursing Home and Orthopedics. The research content mainly focuses on the incidence, influencing factors and prognosis of subsyndromal delirium. Conclusion In recent years, the related literature of subsyndromal delirium abroad has increased step by step, but the number of studies is generally low, and the regional development is unbalanced. Chinese researchers should pay more attention to the topic of subsyndromal delirium. The early identification and nursing intervention programs for Chinese patients are the key research directions in the future. Key words: Subsyndromal delirium; Delirium; Bibliometric analysis

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)0.009
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.062
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.2030.191
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.034
GPT teacher head0.366
Teacher spread0.332 · 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.

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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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Same venue˜The œJournal of practical nursingSame topicIntensive Care Unit Cognitive DisordersFrench-language works237,207