Determination of paternal and maternal parentage in lodgepole pine seed: full versus partial pedigree reconstruction
Bibliographic record
Abstract
Estimating seed orchards’ maternal and paternal gametic contributions is of importance in assessing the genetic quality of seed crops. The advantage of full over partial pedigree reconstruction in investigating the mating dynamics in a lodgepole pine (Pinus contorta Dougl. ex. Loud. ssp. latifolia Engelm.) seed orchard population (N = 74) was demonstrated using nuclear and chloroplast microsatellite markers. We analyzed offspring of equivalent sample sizes representing full (bulk seed with unknown maternal and paternal parentage (n = 635)) and partial (11 maternal family arrays (n = 619)) pedigree reconstruction methods. Small differences in selfing rate, gene flow, and male reproductive success were observed between the two methods; however, the full pedigree reconstruction enabled simultaneous estimation of female-related fertility parameters (female reproductive success and effective number of maternal parents) that partial pedigree reconstruction could not provide. The use of bulk random sample of seed from orchards’ crops is recommended when male and female fertility parameters, as well as selfing and contamination rates, are needed for seed orchards’ seed crops genetic rating.
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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 | 0.003 |
| 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 | 0.000 | 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 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".