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Record W1989901777 · doi:10.1002/pbc.24419

Children's Oncology Group's 2013 blueprint for research: Renal tumors

2012· review· en· W1989901777 on OpenAlexaff
Jeffrey S. Dome, Conrad V. Fernandez, Elizabeth A. Mullen, John A. Kalapurakal, James I. Geller, Vicki Huff, Eric J. Gratias, David Dix, Peter F. Ehrlich, Geetika Khanna, Marcio H. Malogolowkin, James R. Anderson, Arlene Naranjo, Elizabeth J. Perlman

Bibliographic record

VenuePediatric Blood & Cancer · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaIzaak Walton Killam Health Centre
FundersNational Cancer Institute
KeywordsMedicineWilms' tumorRenal cell carcinomaOncologyInternal medicineBlueprintCancerClinical trialClear-cell sarcomaImmunohistochemistry

Abstract

fetched live from OpenAlex

Renal malignancies are among the most prevalent pediatric cancers. The most common is favorable histology Wilms tumor (FHWT), which has 5-year overall survival exceeding 90%. Other pediatric renal malignancies, including anaplastic Wilms tumor, clear cell sarcoma, malignant rhabdoid tumor, and renal cell carcinoma, have less favorable outcomes. Recent clinical trials have identified gain of chromosome 1q as a prognostic marker for FHWT. Upcoming studies will evaluate therapy adjustments based on this and other novel biomarkers. For high-risk renal tumors, new treatment regimens will incorporate biological therapies. A research blueprint, viewed from the perspective of the Children's Oncology Group, is presented.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0150.010

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 head0.086
GPT teacher head0.398
Teacher spread0.312 · 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 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

Citations185
Published2012
Admission routes1
Has abstractyes

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