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Record W2985894798 · doi:10.3390/genes10110879

The RB1 Story: Characterization and Cloning of the First Tumor Suppressor Gene

2019· review· en· W2985894798 on OpenAlexaff
Jesse L. Berry, Ashley Polski, Webster K. Cavenee, Thaddeus P. Dryja, A. Linn Murphree, Brenda L. Gallie

Bibliographic record

VenueGenes · 2019
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersHyundai Hope On WheelsÖgonfondenNational Cancer InstituteChildren's Hospital Los AngelesResearch to Prevent BlindnessKnights Templar Eye Foundation
KeywordsRetinoblastomaGeneticsBiologySuppressorTumor suppressor geneGeneCarcinogenesisCloning (programming)MalignancyComputational biologyComputer science

Abstract

fetched live from OpenAlex

The RB1 gene is the first described human tumor suppressor gene and plays an integral role in the development of retinoblastoma, a pediatric malignancy of the eye. Since its discovery, the stepwise characterization and cloning of RB1 have laid the foundation for numerous advances in the understanding of tumor suppressor genes, retinoblastoma tumorigenesis, and inheritance. Knowledge of RB1 led to a paradigm shift in the field of cancer genetics, including widespread acceptance of the concept of tumor suppressor genes, and has provided crucial diagnostic and prognostic information through genetic testing for patients affected by retinoblastoma. This article reviews the long history of RB1 gene research, characterization, and cloning, and also discusses recent advances in retinoblastoma genetics that have grown out of this foundational work.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.003

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 head0.037
GPT teacher head0.310
Teacher spread0.273 · 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

Citations73
Published2019
Admission routes1
Has abstractyes

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