Quantifying the mechanisms for segmental duplications in mammalian genomes by statistical analysis and modeling
Bibliographic record
Abstract
A large number of the segmental duplications in mammalian genomes have been cataloged by genome-wide sequence analyses. The molecular mechanisms involved in these duplications mostly remain a matter of speculation. To uncover, test, and further quantify the hypotheses on the mechanisms for the recent duplications in the mammalian genomes, we have performed a series of statistical analyses on the sequences flanking the duplicated segments and proposed a dynamic model for the duplication process. The model, when applied to the human duplication data, indicates that approximately 30% of the recent human segmental duplications were caused by a recombination-like mechanism, among which 12% were mediated by the most recently active repeat, Alu. But a significant proportion of the duplications are caused by some mechanism independent of the repeat distribution. A less sure but similar picture is found in the rodent genomes. A further analysis on the physical features of the flanking sequences suggests that one of the uncharacterized duplication mechanisms shared by the mammalian genomes is surprisingly well correlated with the physical instability in the DNA sequences.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Statistical modelling of the molecular mechanisms of segmental duplication in mammalian genomes.
It models mechanisms of mammalian genomic duplication, not research methods or research governance.
Genomics study of mechanisms of mammalian segmental duplications; domain biology.
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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".