A high-density genetic linkage map of a black spruce (<i>Picea mariana</i>) × red spruce (<i>Picea rubens</i>) interspecific hybrid
Bibliographic record
Abstract
Genetic maps provide an important genomic resource of basic and applied significance. Spruce (Picea) has a very large genome size (between 0.85 × 1010 and 2.4 × 1010 bp; 8.5-24.0 pg/1C, a mean of 17.7 pg/1C ). We have constructed a near-saturated genetic linkage map for an interspecific backcross (BC1) hybrid of black spruce (BS; Picea mariana (Mill.) B.S.P.) and red spruce (RS; Picea rubens Sarg.), using selectively amplified microsatellite polymorphic loci (SAMPL) markers. A total of 2284 SAMPL markers were resolved using 31 SAMPL-MseI selective nucleotide primer combinations. Of these, 1216 SAMPL markers showing Mendelian segregation were mapped, whereas 1068 (46.8%) SAMPL fragments showed segregation distortion at α = 0.05. Maternal, paternal, and consensus maps consistently coalesced into 12 linkage groups, corresponding to the haploid chromosome number (1n = 1x = 12) of 12 in the genus Picea. The maternal BS map consisted of 814 markers distributed over 12 linkage groups, covering 1670 cM, with a mean map distance of 2.1 cM between adjacent markers. The paternal BS × RS map consisted of 773 markers distributed over 12 linkage groups, covering 1563 cM, with a mean map distance of 2.0 cM between adjacent markers. The consensus interspecific hybrid BC1 map consisted of 1216 markers distributed over 12 linkage groups, covering 1865 cM (98% genome coverage), with a mean map distance of 1.5 cM between adjacent markers. The genetic map reported here provides an important genomic resource in Picea, Pinaceae, and conifers.
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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 | 0.001 |
| 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) | 0.002 | 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".