Construction of a first genetic map of distylous<i>Turnera</i>and a fine-scale map of the<i>S</i>-locus region
Bibliographic record
Abstract
As a prelude to discovery of genes involved in floral dimorphism and incompatibility, a genetic map of distylous Turnera was constructed along with a fine-scale map of the S-locus region. The genetic map consists of 79 PCR-based molecular markers (48 AFLP, 18 RAPD, 9 ISSR, 4 RAMP), 5 isozyme loci, one additional gene, and the S-locus, spanning a total distance of 683.3 cM. The 86 markers are distributed in 5 linkage groups, corresponding to the haploid chromosome number. Molecular markers tightly linked or co-segregating with the S-locus in an initial mapping population of 94 individuals were used to assay an additional 642 progeny to construct a map of the S-locus region. The fine-scale map consists of 2 markers (IS864a and RP45E9) flanking the S-locus at distances of 0.41 and 0.54 cM, respectively, and 3 additional markers (OPK14c, RP45G18, and RP81E18) co-segregating with the S-locus in the total mapping population of 736 individuals. The genetic map constructed will serve as a framework for localization of genes outside the S-locus affecting distyly, while molecular markers of the fine-scale map will be used to initiate chromosome walking to find the genes residing at the S-locus.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".