Reconstruction of the Synthetic W7984 × Opata M85 wheat reference population
Bibliographic record
Abstract
Reference populations are valuable resources in genetics studies for determining marker order, marker selection, trait mapping, construction of large-insert libraries, cross-referencing marker platforms, and genome sequencing. Reference populations can be propagated indefinitely, they are polymorphic and have normal segregation. Described are two new reference populations who share the same parents of the original wheat reference population Synthetic W7984 (Altar84/ Aegilops tauschii (219) CIGM86.940) x Opata M85, an F(1)-derived doubled haploid population (SynOpDH) of 215 inbred lines and a recombinant inbred population (SynOpRIL) of 2039 F(6) lines derived by single-plant self-pollinations. A linkage map was constructed for the SynOpDH population using 1446 markers. In addition, a core set of 42 SSR markers was genotyped on SynOpRIL. A new approach to identifying a core set of markers used a step-wise selection protocol based on polymorphism, uniform chromosome distribution, and reliability to create nested sets starting with one marker per chromosome, followed by two, four, and six. It is suggested that researchers use these markers as anchors for all future mapping projects to facilitate cross-referencing markers and chromosome locations. To enhance this public resource, researchers are strongly urged to validate line identities and deposit their data in GrainGenes so that others can benefit from the accumulated information.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".