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Record W1819980033 · doi:10.1111/ceo.12132

The genomic landscape of retinoblastoma: a review

2013· review· en· W1819980033 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

VenueClinical and Experimental Ophthalmology · 2013
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsSickKids FoundationPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
FundersNational Center for Advancing Translational Sciences
KeywordsRetinoblastomaEpigeneticsBiologySuppressorGenomicsComputational biologyGenomeGeneCancerTumor suppressor geneGeneticsBioinformaticsCancer researchCarcinogenesis

Abstract

fetched live from OpenAlex

Retinoblastoma is a paediatric ocular tumour that continues to reveal much about the genetic basis of cancer development. Study of genomic aberrations in retinoblastoma tumours has exposed important mechanisms of cancer development and identified oncogenes and tumour suppressors that offer potential points of therapeutic intervention. The recent development of next-generation genomic technologies has allowed further refinement of the genomic landscape of retinoblastoma at high resolution. In a relatively short period of time, a wealth of genetic and epigenetic data has emerged on a small number of tumour samples. These data highlight the inherent molecular complexity of this cancer despite the fact that most retinoblastomas are initiated by the inactivation of a single tumour suppressor gene. This review outlines the current understanding of the genomic, genetic and epigenetic changes in retinoblastoma, highlighting recent genome-wide analyses that have identified exciting candidate genes worthy of further validation as potential prognostic and therapeutic targets.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.104
GPT teacher head0.465
Teacher spread0.360 · 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