Detection and validation of single gene inversions
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
Abstract Motivation: The biologically meaningful algorithmic study of genome rearrangement should take into account the distribution of sizes of the rearranged genomic fragments. In particular, it is important to know the prevalence of short inversions in order to understand the patterns of gene order disruption observed in comparative genomics. Results: We find a large excess of short inversions, especially those involving a single gene, in comparison with a random inversion model. This is demonstrated through comparison of four pairs of bacterial genomes, using a specially-designed implementation of the Hannenhalli–Pevzner theory, and validated through experimentation on pairs of random genomes matched to the real pairs. Availability: The main routines of the experimental software are available through consultation with the authors. Contact: sankoff@uottawa.ca Keywords: short inversions, reversals, genome rearrangement, genome evolution, comparative genomics, bacterial genomes, Hannenhalli--Pevzner algorithm, experimental algorithmics. *To whom correspondence should be addressed.
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) | 0.000 | 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