Lethals can be estimated from doubled haploid <i>Larix decidua </i>female gametophytes
Bibliographic record
Abstract
We present a novel way of estimating embryo lethals using doubled haploid (dihaploid or DH) female gametophytes grown in tissue culture. This DH-based lethals estimate is hypothesized to be lower than the more common method where lethals are estimated from one generation of selfing. The chief reasoning is the early mortality spike observed for selfed embryos of larch and other genera in the Pinaceae. This early mortality spike occurs at the stage when diploid embryos embed into haploid female gametophyte tissue. However, this stage is missing for DH embryos which grow in a petri dish thus the DH lethals estimate is hypothesized to be lower compared to seed counts. This DH estimate is based on 20,000 haploid female gametophytes cultures from which two surviving diploidized embryos were recovered. Lethals based on diploidized haploids (DH) have not been reported for a conifer previously because, aside from larch, only a few conifer species continue female gametophyte development in absence of pollen. Our chief finding is that, contrary to our hypothesis, the DH-based lethals estimate was similar to lethals estimated obtained from selfed seeds in published studies. Thus doubling haploid female gametophytes can be used to estimate embryo lethals when diploidization is conducted on a massive scale.
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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 | 0.000 |
| 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) | 0.002 | 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".