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Record W4388648049 · doi:10.21203/rs.3.rs-3593556/v1

Hospice Care in Pediatrics

2023· preprint· en· W4388648049 on OpenAlexaff
Jumei Pan, Khan Akhtar Ali

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsHealth Care Foundation
Fundersnot available
KeywordsPediatricsMedicineFamily medicine

Abstract

fetched live from OpenAlex

Abstract Background Hospice care is the primary field of public health that establishes the minimum standards of care for patients who are nearing the end of their lives. All individuals, irrespective of their race, social status, or cultural heritage, should be able to obtain this healthcare. Scientific literature has brought attention to the inequalities in healthcare based on race and ethnicity. The focus of this article is to examine previous research on the impact of hospice care on infected children, parents, and siblings. Providing hospice care can help children maintain a positive attitude during their treatment. Objective The review is based on prior research, and extensive investigation is being made into pediatric hospice care. Methods Various keywords were utilized for the research. PubMed, Medline, and other scientific sources were utilized to ensure the accuracy of the collected scientific research data. The collected data underwent inclusion and exclusion criteria. Ultimately, twenty-seven articles were chosen. Results From 2015 to 2022, 27 studies were conducted involving 115 families. The findings showed the positive impact of hospice care on both parents and children. Additionally, the research also delved into the specific needs of children in hospice care. Conclusion Children who receive hospice care tend to have a better quality of life.

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)0.001
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.194
GPT teacher head0.518
Teacher spread0.324 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

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