Bibliographic record
Abstract
Cancer is a disease that involves genomic instability, to which c-Myc contributes during its initiation and progression. Over 70% of all human cancers show deregulated levels of c-Myc protein. The term genomic instability refers to genetic and/or epigenetic changes that alter the normal organization and function of genes and chromosomes. Genomic instability is a hallmark of cancer and often is associated with cancer. Deregulated c-Myc expression generates genomic instability by initiating intra- and extrachromosomally locus-specific gene amplification, gene rearrangements and karyotypic instability that includes translocations, fusions, insertions and deletions. Out of the several outlined pathways by which deregulated levels of c-Myc can lead to genomic instability, the work described in this thesis focuses on three with direct relevance to tumorigenesis; gene amplification (increase in gene copy number), remodeling of the chromosomal and telomeric structures in the interphase nucleus and comparing the effect of Myc to that of Epstein Bar virus (EBV) infection in remodeling the nuclear structure that may lead to genomic instability.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".