A comparative study of the floras of China and Canada
Bibliographic record
Abstract
ABSTRACT In this study, we investigated the floristic relationships between China and Canada based on comparative analysis of their spermatophyte floras. Floristic lists were compiled from standard floras and then subjected to cluster analysis using UPGMA and NMS ordination methods. Our data demonstrate that the Chinese spermatophyte flora is considerably more diverse than that of Canada and that the taxonomic richness of seed plants in the floras of China and Canada shows significant variation at the specific and generic levels. China contains 272 families, 3 318 genera, and 27 078 species (after taxonomic standardization), whereas the spermatophyte flora of Canada includes 145 families, 947 genera, and 4 616 species. The results indicate that out of 553 genera shared by the Chinese and Canadian floras, 60 of them have an eastern Asia-North American disjunct distributional pattern. These disjunct genera show a similar geographic distribution in both eastern and western Canada. There is a higher degree of similarity at higher taxonomic levels between the two intercontinental floras, which suggests ancient floristic relationships, but there are significant differences at the generic and specific levels that are correlated with more recent geological and climatic variations and ecoenvironment diversity, resulting in differences in floristic composition. Overall, western and eastern Canada have a similar number of shared genera, which suggests multiple migration events of floristic elements via the Atlantic and Pacific connections and corridors that existed in past geological times.
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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 | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".