Morphological and genetic differentiation in <i>Isodon umbrosus</i> by altitudinal variation in bumblebee pollinator assemblages
Bibliographic record
Abstract
Abstract The corolla tube length of the bumblebee‐pollinated plant Isodon umbrosus shows conspicuous geographical variation, corresponding with the proboscis length of its bumblebee pollinators across its distributional range. We hypothesized that altitudinal variation in the pollinator assemblage is a principal factor mediating morphological and genetic differentiation among I. umbrosus populations. We examined determinants of the morphological and genetic differentiation of Isodon umbrosus by analyzing floral morphology and allozyme variation across the distributional range. A reanalysis of previous data confirmed that altitude was a good indicator of pollinator assemblages. Corolla tube length was highly variable among the 15 study populations, and genetic differentiation among the populations ( G ST = 0.360) was also highly significant. The differentiation in corolla tube length was explained by altitudinal difference, a proxy of the difference in pollinator assemblages. Genetic differentiation among populations also tended to be affected by the same factor, but statistical support was weak. To better understand the mechanisms responsible for morphological and genetic differentiation in I. umbrosus , we need to investigate altitudinally different populations over a narrower geographical scale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".