A molecular marker associated with low-temperature induction of dormancy in red osier dogwood (Cornus sericea)
Bibliographic record
Abstract
Dormancy induction in temperate deciduous plants is thought to be regulated by short photoperiods, but low temperature has been shown to eliminate the short photoperiod requirement in northern ecotypes. An F2 population (191 plants) red osier dogwood (Cornus sericea L.) derived from a polycross of an F1 population produced from reciprocal crosses of the parental clonal ecotypes, Northwest Territories (NWT, 62 degrees N) and Utah (42 degrees N), was examined to identify molecular markers of temperature-induced endodormancy. Dormancy induction curves were generated for each individual in the F2 population and a standard point prior to vegetative maturity (i-VM) was inferred from the change in slope of the dormancy acquisition curve. Under Saskatoon, Saskatchewan field conditions (52 degrees N), the NWT ecotype entered i-VM on average 5-6 weeks before the Utah ecotype. Two sub-populations of the F2 population were distinguishable based on VM acquisition on exposure to low temperature but not to short photoperiods. A sequence characterized amplified region (SCAR) marker was developed that correctly (> 92%) identified individual plants within the F2 subpopulation that were responsive to low-temperature induction of VM. Timing of bud break was strongly associated with the timing of VM in the geographical ecotypes but not in the F2 population, indicating that these are separate traits under genetic control.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".