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Record W1987558888 · doi:10.1053/jpon.2003.2

Pain Practices: A Cross-Canada Survey of Pediatric Oncology Centers

2003· article· en· W1987558888 on OpenAlexaffabout
Jacqueline A. Ellis, Patricia McCarthy, Linda Hershon, Rosemary Horlin, Marion Rattray, Sally Tierney

Bibliographic record

VenueJournal of Pediatric Oncology Nursing · 2003
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCancer painPain managementMedicinePediatric oncologyFamily medicineBest practicePediatric cancerPain assessmentCancerSurvey data collectionPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Before implementing a pain education program, the Canadian Association of Nurses in Oncology conducted a national survey on cancer pain management. The survey focused primarily on adult cancer pain and a second survey was undertaken to describe the supports in place across Canada for best practice pediatric cancer pain management. Twenty-eight pediatric cancer centers responded to a survey that was composed of 48 questions about the types of supports that are in place related to pain assessment, management, and pain-related staff and family education. Results of the survey indicated that, for the most part, children have access to the components of best practice pain management. In addition, areas of strength and areas that need to be further developed were identified and the implications for the findings discussed.

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 score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.395
Teacher spread0.343 · 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

Citations19
Published2003
Admission routes2
Has abstractyes

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