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Record W1837292249 · doi:10.1002/pbc.24858

Beyond the bench and the bedside: Economic and health systems dimensions of global childhood cancer outcomes

2013· article· en· W1837292249 on OpenAlexaff
Avram Denburg, Felícia Marie Knaul, Rifat Atun, Lindsay A. Frazier, Ronald D. Barr

Bibliographic record

VenuePediatric Blood & Cancer · 2013
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster UniversityHospital for Sick Children
Fundersnot available
KeywordsMedicineChildhood cancerGlobeGlobal healthBlood cancerCancerPediatric cancerHealthcare systemPoliticsEconomic growthHealth carePublic healthNursingPolitical science

Abstract

fetched live from OpenAlex

Globally, the number of new cases of childhood cancer continues to rise, with a widening gulf in outcomes across countries, despite the availability of effective cure options for many pediatric cancers. Economic forces and health system realities are deeply embedded in the foundation of disparities in global childhood cancer outcomes. A truly global effort to close the childhood cancer divide therefore requires systemic solutions. Analysis of the economic and health system dimensions of childhood cancer outcomes is essential to progress in childhood cancer survival around the globe. The conceptual power of this approach is significant. It provides insight into how and where pediatric oncology entwines with broader political and economic conditions, and highlights the mutual benefit derived from systems-oriented solutions.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.010
Scholarly communication0.0100.012
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.305
Teacher spread0.290 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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