Towards an expanded and integrated linkage map of cucumber (<i>Cucumis sativus</i> L.)
Bibliographic record
Abstract
Linkage maps in cucumber (Cucumis sativus var. sativus L.) have been constructed using morphological traits, isozymes, restriction fragment length polymorphisms (RFLPs), and random amplified polymorphic DNAs (RAPDs). The lack of polymorphism in cucumber has led to the construction of relatively unsaturated maps (13- to 80-point). We have added amplified fragment length polymorphism (AFLP) markers to existing narrow-based (within C. sativus) and wide-based (C. sativus x C. sativus var. hardwickii) maps. JOINMAP v. 2.0 was used to construct maps and to join these with historical maps from several previous studies. Our narrow- and wide-based merged maps contain 255 and 197 markers, respectively, including morphological traits, disease resistance loci, isozymes, RFLPs, RAPDs, and AFLPs. Condensation of total map distance occurred in merged maps compared to historic maps using many of the same markers. This phenomenon is most likely due to differences in map construction algorithms. The merged maps represent the best fit of the data used and are an important first step towards the construction of a comprehensive linkage map for cucumber. Identification of additional anchor markers between the narrow- and wide-based maps presented here may allow their future integration into a unified model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".