Genetic structure and migration from mainland to island populations in<i>Abies procera</i>Rehd
Bibliographic record
Abstract
Noble fir (Abies procera Rehd) is a narrowly distributed conifer with a typical mainland-island structure of natural distribution. Here, we examined the genetic structure of populations native to the Pacific coast from Oregon to Washington (5 island and 16 mainland populations) with 14 polymorphic allozyme loci. A general method for estimating the number of unidirectional migrants from the mainland to island populations is presented in terms of the relation of average heterozygosity between the mainland and island populations. The results indicated that there were substantial island-mainland population differentiations (Fst = 0.107+/-0.029~0.154+/-0.039) but small differentiation within the mainland/submainland populations (0.037+/-0.008 approximately 0.054+/-0.010). Significant isolation by distance existed among the island-mainland populations and among the populations in Washington submainland. Four islands investigated received different numbers of migrants from the mainland/submainland. The southern island populations received a smaller number of migrants from the mainland but had greater genetic diversity, implying that there could be introgression with A. magnifica and (or) they represented possible glacial refuges and had expanded northwards after the last glaciations. The island populations close to the Pacific coast were more likely mainland-dependent.
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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 | 0.000 | 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) | 0.001 | 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".