Data from: Inbreeding depression in intra-provenance crosses driven by founder relatedness in white spruce
Bibliographic record
Abstract
Genetic means for height growth differed between intra- and inter-provenance crosses, which we hypothesized was due partly to unidentified relatedness among intra-provenance base parents resulting in mild inbreeding and inbreeding depression among their offspring. A dense array of 5,844 single nucleotide polymorphisms was used to directly construct a genomic relationship matrix (G) that had four elements ranging from 0.17 to 0.24, between five intra-provenance base parents. Adjusting the numerator relationship matrix for this relatedness among base parents produced inbreeding coefficients of F i ≈ 0.1 in their offspring, which displayed depressed height growth. Accounting for inbreeding level as a covariate in a mixed model decreased grossly overestimated (up to 2 ×) dominance variance in models without the covariate adjustment. Height growth decreased 39 cm (∼ 6 %) for every 0.1 increase in F i .
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.024 |
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".