Bibliographic record
Abstract
BACKGROUND: Median construction is at the heart of several approaches to gene-order phylogeny. It has been observed that the solution to a median problem is generally not unique, and that alternate solutions may be quite different. Another concern has to do with a tendency for medians to fall on or near one of the three input orders, and hence to contain no information about the other two. RESULTS: We conjecture that as gene orders become more random with respect to each other, and as the number of genes increases, the breakpoint median for circular unichromosomal genomes, in both the unsigned and signed cases, tends to approach one of the input genomes, the "corners" in terms of the distance normalized by the number of genes. Moreover, there are alternate solutions that approach each of the other inputs, so that the average distance between solutions is very large. We confirm these claims through simulations, and extend the results to medians of more than three genomes. CONCLUSIONS: This effect also introduces serious biases into the medians of less scrambled genomes. It prompts a reconsideration of the role of the median in gene order phylogeny. Fortunately, for triples of finite length genomes, a small proportion of the median solutions escape the tendency towards the corners, and these are relatively close to each other. This suggests that a focused search for these solutions, though they represent a decreasing minority as genome length increases, is a way out of the pathological tendency we have described.
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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 | 0.007 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".