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Record W2907896064 · doi:10.18632/oncotarget.26524

Multidimensional intratumour heterogeneity in neuroblastoma

2019· editorial· en· W2907896064 on OpenAlexaff
Kristoffer von Stedingk, David Gisselsson, Daniel Bexell

Bibliographic record

VenueOncotarget · 2019
Typeeditorial
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMedicineComputational biologyNeuroblastomaCancer researchOncologyBioinformaticsInternal medicineBiologyGeneticsCell culture

Abstract

fetched live from OpenAlex

Neuroblastoma (NB) is a solid childhood cancer originating from the sympathetic nervous system.Most NBs arise from the adrenal gland but metastases to distant sites such as bone marrow, liver and lungs are not uncommon.Despite intense treatment, including highdose chemotherapy, many high-risk NBs relapse and treatment resistance is a significant clinical problem.NB is a heterogeneous disease, i.e., tumours display high inter-tumour heterogeneity.Recent findings also point to genetic intratumour heterogeneity (ITH) in NB, albeit www.oncotarget.com

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)0.003
metaresearch head score (Gemma)0.006
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0050.004

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 head0.011
GPT teacher head0.312
Teacher spread0.301 · 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
GenreEditorial

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

Citations13
Published2019
Admission routes1
Has abstractyes

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