Asian relationships of the flora of the European Alps
Bibliographic record
Abstract
Background: It has long been recognised that the Alps have strong biogeographical links to Asia. Aims: We investigate here whether the two areas are connected either through southern (mountain chains between the Alps and the Himalayas) or through northern regions. Methods: We compiled the geographical distribution of plant genera growing both in the Alps and the Himalayas, and outside these two regions. This compilation was used to search for molecular phylogenetic literature which was screened for area relationships informative for our purposes. Results: Of 933 genera growing in the Alps, 653 were considered further. Of the 429 genera growing in the Alps and the Himalayas, 218 grow in both northern and southern intervening areas, 203 only in southern intervening areas, three only in northern intervening areas, and five in the Alps and Himalayas but not in between. Epimedium, Primula sect. Auricula and Scopolia can be considered examples for a northern connection. Brachypodium, Poaceae subtribe Loliinae, Bupleurum, Doronicum and Atropa are examples for a southern connection. In the latter group centres of diversity are clearly located in the Mediterranean area and occurrences further east appear to be derived. Conclusions: Although our database is very narrow, we predict that ideas about the biogeographical composition of the flora of the Alps made by several early authors will be confirmed. It will be found to contain a northern element originating from Asia via a northern connection, and a southern element originating from the Mediterranean area or southwest Asia.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".