Geographic variation in chloroplast haplotypes in the California red fir-noble fir species complex and the status of Shasta red fir
Bibliographic record
Abstract
I present the results of a molecular investigation into taxonomically unresolved issues of the California red fir – noble fir species complex. Samples were collected throughout the range of California red fir ( Abies magnifica A. Murray), from the southern Sierra Nevada to the region in northern California and southern Oregon where morphological variation has suggested it hybridizes with noble fir ( Abies procera Rehder). Two rbcL sequences were found within A. magnifica and showed perfect linkage with variation at the chloroplast trnD locus. Only populations in the region of hypothesized hybridization were polymorphic for rbcL. One haplotype is unique to A. magnifica in the southern part of its range, and the other is identical to that found in A. procera to the north, supporting a broad zone of hybridization. There was no evidence for a cryptic geographic barrier between the two species. A single A. procera tree from southwestern Washington also had the A. magnifica haplotype, suggesting that introgression from A. magnifica may be widespread. The type locality of Abies magnifica var. shastensis Lemmon was polymorphic, whereas the disjuct southern A. magnifica var. shastensis was monomorphic for rbcL. I also present corrections, based on replication, to two rbcL sequences for A. magnifica previously deposited in GenBank.
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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) | 0.001 | 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".