Estimating meiotic chromosome pairing and recombination parameters in telocentric trisomics
Bibliographic record
Abstract
Telocentric trisomics (telotrisomics; one arm of a metacentric chromosome present in addition to two complete genomes) are used in theoretical studies of pairing affinities and chiasma formation in competitive situations and applied in genome analysis, gene localization, gene transfer, and breakage of close linkages. These applications require knowledge of the recombination characteristics of telotrisomics. Appropriate cytological and molecular markers and favorable chromosome morphology are not always available or applicable for quantitative analyses. We developed new mathematical models for extracting the maximum information from simple metaphase I observations. Two types of telotrisomics of the short arm of chromosome 1R of rye (Secale cereale), including several genotypes, were used as test material. In simple telotrisomics, pairing between morphologically identical complete chromosomes was more frequent than pairing between the telocentric and either of the normal chromosomes. In the telocentric substitution, morphologically identical telocentrics paired less frequently with each other than either one with the normal chromosome. Pairing partner switch was significant. Interaction between the two arms was variable. Variation within plants was considerable. Telotrisomics without markers are suitable for analyzing pairing preferences, for gene localization and gene transfer, and for breaking tight linkages, but less so for genome analysis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".