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Record W2922442128 · doi:10.1126/science.aaw4892

Science and health for all children with cancer

2019· review· en· W2922442128 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2019
Typereview
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersAmerican Lebanese Syrian Associated Charities
KeywordsMultidisciplinary approachAbandonment (legal)Childhood cancerMedicineLow and middle income countriesCancerGlobal healthChild survivalEnvironmental healthFamily medicineEconomic growthDeveloping countryPolitical scienceSurvivorship curvePublic healthNursingInternal medicineEconomics

Abstract

fetched live from OpenAlex

Each year ~429,000 children and adolescents aged 0 to 19 years are expected to develop cancer. Five-year survival rates exceed 80% for the 45,000 children with cancer in high-income countries (HICs) but are less than 30% for the 384,000 children in lower-middle-income countries (LMICs). Improved survival rates in HICs have been achieved through multidisciplinary care and research, with treatment regimens using mostly generic medicines and optimized risk stratification. Children's outcomes in LMICs can be improved through global collaborative partnerships that help local leaders adapt effective treatments to local resources and clinical needs, as well as address common problems such as delayed diagnosis and treatment abandonment. Together, these approaches may bring within reach the global survival target recently set by the World Health Organization: 60% survival for all children with cancer by 2030.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.155
GPT teacher head0.476
Teacher spread0.321 · 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