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Record W4409690039 · doi:10.1158/1538-7445.am2025-1206

Abstract 1206: The molecular characterization initiative: Nationwide comprehensive clinical profiling of pediatric solid tissue malignancies at scale

2025· article· en· W4409690039 on OpenAlexaboutno aff
Elaine R. Mardis

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProfiling (computer programming)MedicinePathologyComputer science

Abstract

fetched live from OpenAlex

Abstract The Molecular Characterization Initiative is an NCI-sponsored program being conducted in collaboration with the Children’s Oncology Group (COG), that seeks to enroll cancer patients from ages 0-25 with a primary diagnosis of a CNS malignancy, soft-tissue sarcoma, rare cancer or high-risk neuroblastoma onto Project Every Child. Subsequent to enrollment, the submission of a disease-involved specimen (cancer) and matched comparator normal (blood or buccal) is subjected to DNA and RNA (tumor) or DNA (normal) extraction by the Biopathology Center, followed by comprehensive clinical molecular profiling at The Institute for Genomic Medicine. To-date, over 4100 patients from 27 states in the United States, from Canada, Australia and New Zealand have been enrolled and studied since project inception in March 2022. Each patient sample set is evaluated by comparative tumor:normal exome analysis, fusion/ITD panel testing of RNA and by DNA methylation profiling, with return of results within 21 days from receipt of specimens at Nationwide Children’s Hospital. Subsequent to return of clinical results, each patient’s data are de-identified and submitted to the Childhood Cancer Database, a public repository managed by the NCI. The data in this repository are publicly available, with institutional sign-off, for the purposes of fueling future discoveries impacting pediatric cancer. The size and scope of the Molecular Characterization Initiative will be equivalent to or greater than other large-scale clinical profiling efforts conducted in Germany (INFORM) and in Australia (Zero Childhood Cancer). The current status and unique results from the MCI will be presented, along with future plans and ongoing challenges. Citation Format: Elaine R. Mardis, On behalf of The Institute for Genomic Medicine at Nationwide Children's Hospital. The molecular characterization initiative: Nationwide comprehensive clinical profiling of pediatric solid tissue malignancies at scale [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1206.

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 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.131
GPT teacher head0.491
Teacher spread0.359 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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