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Record W3137166270 · doi:10.3390/children8030250

Quality Indicators in Pediatric Palliative Care: Considerations for Latin America

2021· review· en· W3137166270 on OpenAlexaff
Gregorio Zúñiga-Villanueva, Jorge Alberto Ramos-Guerrero, Mónica Osio-Saldaña, Jessica Casas, Joan Marston, Regina Okhuysen‐Cawley

Bibliographic record

VenueChildren · 2021
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPalliative careLatin AmericansSociocultural evolutionContext (archaeology)Quality (philosophy)MedicineNursingBusinessPolitical scienceGeography

Abstract

fetched live from OpenAlex

Pediatric palliative care is a growing field in which the currently available resources are still insufficient to meet the palliative care needs of children worldwide. Specifically, in Latin America, pediatric palliative care services have emerged unevenly and are still considered underdeveloped when compared to other regions of the world. A crucial step in developing pediatric palliative care (PPC) programs is delineating quality indicators; however, no consensus has been reached on the outcomes or how to measure the impact of PPC. Additionally, Latin America has unique sociocultural characteristics that impact the perception, acceptance, enrollment and implementation of palliative care services. To date, no defined set of quality indicators has been proposed for the region. This article explores the limitations of current available quality indicators and describes the Latin American context and how it affects PPC development. This information can help guide the creation of standards of care and quality indicators that meet local PPC needs while considering the sociocultural landscape of Latin America and its population.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.102
GPT teacher head0.420
Teacher spread0.318 · 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.

Study designNot applicable
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

Citations14
Published2021
Admission routes1
Has abstractyes

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