Potential Hybridization of Genetically Engineered Triticale with Wild and Weedy Relatives in Canada
Bibliographic record
Abstract
Triticale (xTriticosecale Wittmack) is a promising cereal platform for novel bioindustrial products being developed using genetic engineering (GE). Before GE crop varieties are approved in Canada, the potential for gene flow to wild and weedy relatives must be examined. To identify at‐risk species for hybridization and gene flow, we reviewed the phylogeny of triticale relatives, outcrossing barriers, reported crosses, and occurrence of wild relatives in Canada. Presence of genes that inhibit outcrossing, genome constitution, geographic distribution, and floral structure influence triticale hybridization potential. Hybridization experiments between triticale and parental species indicate crosses may produce viable seeds, although outcrossing with rye (Secale cereale L.) is less likely. With respect to nonparental species that occur in Canada, jointed goatgrass (Aegilops cylindrica Host) and intermediate wheatgrass (Agropyron intermedium (Host) Beauv.) should be investigated to determine if viable hybrids with triticale can occur. While there are reports of wheat (Triticum spp.) hybridization with pubescent wheatgrass [Agropyron trichophorum (Link) K. Richt.], quackgrass [Elymus repens (L.) Gould], barley (Hordeum vulgare L.), and lyme grass (Leymus arenarius Hochst), hybridization with triticale under natural conditions seem unlikely.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".