Carici arctisibiricae–Hylocomietea alaskani – a new class of zonal tundra vegetation
Bibliographic record
Abstract
A new class, Carici arctisibiricae–Hylocomietea alaskani class nov. is described for vegetation of the tundra zone on a circumpolar scale. This higher unit in the system of Braun-Blanquet floristic (= floristic-sociological) classification unites the zonal vegetation in the intermediate habitats with respect to the substrate moisture, pH and texture, the snow cover thickness and duration, the depth of seasonal frozen ground thawing, and the growing season length on the interfluves (upland surfaces) within the tundra zone (CAVM subzones B, C, D, E = arctic, typical and southern tundra subzones in Russian zonal subdivision). Communities of the class are distributed on plains north of the tree line on two continents (Eurasia and North America), as well as on the archipelagos (Spitsbergen, Novaya Zemlya, New Siberian Islands, the Canadian Arctic Archipelago) and the large and small islands (Kolguev, Dolgy, Vaygach, Bely, Bolshoy Begichev, Ayon, Wrangel, Greenland) in the Arctic Ocean. The class comprises 3 new orders and 6 alliances. The diagnoses of higher rank units are given. Difficulties in describing and classifying zonal communities due to the specificity of their species composition and horizontal and vertical structure are discussed. The criteria distinguishing the new class from the known ones in the Europe and Asia mountains, in which zonal tundra communities are being placed until now, are presented.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".