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Record W4396522020 · doi:10.5737/23688076342215

Supportive care services in New Brunswick, Canada: An environmental scan

2024· article· en· W4396522020 on OpenAlexaffvenueabout
Charlotte Schwarz, Alison Luke, Lauren Renée Ashfield, Julie Easley, Stephanie McIntosh-Lawrence, Danie Beaulieu, Shelley Doucet

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsHorizon Health NetworkSaint John Regional HospitalUniversity of FrederictonUniversity of New Brunswick
Fundersnot available
KeywordsBusinessPolitical science

Abstract

fetched live from OpenAlex

Cancer diagnosis and treatment often have significant physical and psychological implications for both the survivor and their family/caregivers. Necessary services extend beyond medical treatment and include a variety of supportive care services (SCS) that address individuals' physical, social, educational, and emotional needs. This study seeks to map the SCS available in the province of New Brunswick (NB), Canada, for cancer survivors, their families, and their caregivers. An environmental scan was conducted to assess current SCS available in NB. While some SCS exist in NB, they are not always easily accessible or identifiable, and gaps in services were prevalent. In particular, a gap in services was found for individuals who are no longer actively receiving cancer treatment, as well as for family members and caregivers.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.557

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.013
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.357
Teacher spread0.339 · 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 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".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

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