Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tumorigenesis can be viewed as an imbalance between the mechanisms of cell-cycle control and mutation rates within the genes. Genomic instability is broadly classified into microsatellite instability (MIN) associated with mutator phenotype, and chromosome instability (CIN) recognized by gross chromosomal abnormalities. Three intracellular mechanisms are involved in DNA damage repair that leads to mutator phenotype. They include the nucleotide excision repair (NER), base excision repair (BER) and mismatch repair (MMR). The CIN pathway is typically associated with the accumulation of mutations in tumor suppressor genes and oncogenes. Defects in DNA MMR and CIN pathways are responsible for a variety of hereditary cancer predisposition syndromes including hereditary non-polyposis colorectal carcinoma (HNPCC), Bloom syndrome, ataxia-telangiectasia, and Fanconi anaemia. While there are many genetic contributors to CIN and MIN, there are also epigenetic factors that have emerged to be equally damaging to cell-cycle control. Hypermethylation of tumor suppressor and DNA MMR gene promoter regions, is an epigenetic mechanism of gene silencing that contributes to tumorigenesis. Telomere shortening has been shown to increase genetic instability and tumor formation in mice, underscoring the importance of telomere length and telomerase activity in maintaining genomic integrity. Mouse models have provided important insights for discovering critical pathways in the progression to cancer, as well as to elucidate cross talk among different pathways. This review examines various molecular mechanisms of genomic instability and their relevance to cancer.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it