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Record W1986542724 · doi:10.1002/jcb.21846

Nuclear microenvironments and cancer

2008· article· en· W1986542724 on OpenAlexaff
Gary S. Stein, James Davie, J. Randy Knowlton, Sayyed K. Zaidi

Bibliographic record

VenueJournal of Cellular Biochemistry · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsResearch Manitoba
FundersNational Cancer Institute
KeywordsBiologyComputational biologyCarcinogenesisCancerProteomicsCompartmentalization (fire protection)GenomicsFunctional genomicsGeneCell biologyGeneticsGenomeBiochemistry

Abstract

fetched live from OpenAlex

Nucleic acids and regulatory proteins are architecturally organized in nuclear microenvironments. The compartmentalization of regulatory machinery for gene expression, replication and repair, is obligatory for fidelity of biological control. Perturbations in the organization, assembly and integration of regulatory machinery have been functionally linked to the onset and progression of tumorigenesis. The combined application of cellular, molecular, biochemical and in vivo genetic approaches, together with structural biology, genomics, proteomics and bioinformatics, will likely lead to new approaches in cancer diagnostics and therapy.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.186
Teacher spread0.182 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2008
Admission routes1
Has abstractyes

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