Relationship between empty seed and genetic factors in European beech (Fagus sylvatica L.)
Why this work is in the frame
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Bibliographic record
Abstract
<ja:p>The relationship between percentage of empty seed (Pes) and genetic factors was explored in an isolated stand of European beech (Fagus sylvatica L.). Nine allozyme loci (GOT-B, IDH-A, LAP-A, MDH-B, MDH-C, MNR-A, 6-PGDH-A, PGI-B and PGM-A) were used to estimate genetic factors. Pes ranged from 4.8% to 40.9% for seed samples of 91 trees within the stand and showed an approximate normal distribution. The average Pes was 21.4% and the repeatability of Pes was 43.4%. The multilocus estimate for outcrossing rate (tm) based on seed samples of 30 trees within the stand was 1.015 (SE = 0.011) and the mean single locus estimate was slightly higher at 1.061 (SE = 0.026). No evidence of biparental inbreeding was found. Weak positive correlation between Pes and maximum selfing rate as well as and significant negative correlation between Pes and multilocus outcrossing rate indicated that self-fertilization may be explained as one of the important causes of empty seeds in beech.</ja:p>
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it