From comparative gene content and gene order to ancestral contigs, chromosomes and karyotypes
Bibliographic record
Abstract
To reconstruct the ancestral genome of a set of phylogenetically related descendant species, we use the RACCROCHE pipeline for organizing a large number of generalized gene adjacencies into contigs and then into chromosomes. Separate reconstructions are carried out for each ancestral node of the phylogenetic tree for focal taxa. The ancestral reconstructions are monoploids; they each contain at most one member of each gene family constructed from descendants, ordered along the chromosomes. We design and implement a new computational technique for solving the problem of estimating the ancestral monoploid number of chromosomes x. This involves a "g-mer" analysis to resolve a bias due long contigs, and gap statistics to estimate x. We find that the monoploid number of all the rosid and asterid orders is [Formula: see text]. We show that this is not an artifact of our method by deriving [Formula: see text] for the metazoan ancestor.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".