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Record W3085341517 · doi:10.38124/ijisrt20sep086

Hand Hygiene Guidelines for Front Line Health Care Workers

2020· article· en· W3085341517 on OpenAlexaboutno aff
Bhavanam Sai Rajendra

Bibliographic record

VenueInternational Journal of Innovative Science and Research Technology (IJISRT) · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsHygieneFront lineMedicineHealth careNursingFamily medicineData collectionPersonal protective equipmentEnvironmental healthCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Hand hygiene competence is one of the critical outcomes for health care workers who are working for covid patients.. Ensuring health care workers to reduce the risk of infections among nurses and health care workers. Adequate hand hygiene(HH) awareness for hospital staff like Nurses, ward technicians, health care workers should be implemented so as to reduce risks of facing infections. To assess the knowledge and awareness programmes to the front line warriors who are in direct contact with covid patients. A systematic review of studies published on January 1, 2009 based on, an online survey done in Canada where FIVE leading hospitals are actively involved and participated for Hand hygiene care. An online Data collection with simple and sample survey was conducted for Nurses, ward technicians, covid health care workers and Gram volunteers according to Guidelines given by World Health Organization’s SEVEN ( 7) hand washing steps. The Data collection was taken from 50 Nurses and 50 covid health care workers particularly working in rural areas of Parchur Mandal of Prakasam District in Andhra Pradesh state

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.301
GPT teacher head0.595
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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