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Record W1546380214 · doi:10.1002/9780470513750.ch6

Loss of Genetic Information in Cancer

2007· article· en· W1546380214 on OpenAlexaff
Webster K. Cavenee, Marc F. Hansen, Heidi Scrable, C. David James

Bibliographic record

VenueNovartis Foundation symposium · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsRoyal Victoria Regional Health CentreRoyal Victoria Hospital
Fundersnot available
KeywordsRetinoblastomaHepatoblastomaBiologyLocus (genetics)GeneticsLoss of heterozygosityAlleleCancerWilms' tumorChromosomeGenotypeCancer researchSarcomaRhabdomyosarcomaCytogeneticsPathologyGeneMedicineInternal medicine

Abstract

fetched live from OpenAlex

The determination and comparison of genotypic combinations at genomic loci in normal and tumour tissues from patients with various types of cancer have defined the chromosomal locations of loci at which recessive mutations play a role in disease. The predisposing nature of some of these mutant alleles is exemplified in studies of retinoblastoma and osteogenic sarcoma. These two clinically associated diseases share a pathogenetically causal predisposition that maps to chromosome position 13q14. A similar mechanism at 11p15.5 is involved in the development of the embryonal variant of rhabdomyo-sarcoma, Wilms' tumour and hepatoblastoma. Finally, genomic alteration of chromosome 10 is apparent in glioblastomas and mixed tumours of glioblastoma/astrocytoma grade III but not in homogenous astrocytoma grades II or III, suggesting the definition of a locus involved in tumour progression and, perhaps, an approach to molecular genetic staging of tumours.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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
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

Citations11
Published2007
Admission routes1
Has abstractyes

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