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Record W1990860457 · doi:10.1159/000133261

Mechanisms of loss of heterozygosity in retinoblastoma

2008· article· en· W1990860457 on OpenAlexaff
Xiao‐Dong Zhu, James M. Dunn, Audrey D. Goddard, Jeremy A. Squire, A Becker, Robert A. Phillips, Brenda L. Gallie

Bibliographic record

VenueCytogenetics and Cell Genetics · 2008
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsLoss of heterozygosityRetinoblastomaBiologyMitotic crossoverGermline mutationSomatic cellCancer researchGermlineChromosomeAlleleGeneticsMutationMitosisMolecular biologyGene

Abstract

fetched live from OpenAlex

Retinoblastoma (RB) tumors arise when both alleles of the RB1 gene are inactivated by two mutational events (M1 and M2). M1 can be an initial germline or somatic mutation; M2 is frequently loss of heterozygosity (LOH), which makes the cell homozygous or hemizygous for the original mutation. LOH is the major mechanism by which many cancers are initiated. To further delineate the mechanism of LOH, we screened a total of 37 RB tumors for LOH by Southern blot analysis. The tumors were from 17 bilaterally and 17 unilaterally affected patients. Nineteen of 30 informative tumors (63%) from 27 patients showed LOH. Proximal and distal flanking markers on chromosome 13 were informative in 13 tumors, allowing evaluation of the mechanisms by which LOH occurred. Mitotic recombination was implicated in 6 (46%) of the 13 tumors.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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 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

Citations106
Published2008
Admission routes1
Has abstractyes

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