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Record W4318274215 · doi:10.17581/bp.2023.12106

Carici arctisibiricae–Hylocomietea alaskani – a new class of zonal tundra vegetation

2023· article· en· W4318274215 on OpenAlexaboutno aff
N. V. Matveyeva, O. V. Lavrinenko

Bibliographic record

VenueBotanica Pacifica · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTundraArchipelagoFloristicsVegetation (pathology)ArcticPhysical geographyGeographyTree lineGeologyClimatologyEcologyOceanographyPaleontologySpecies richnessClimate change

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.025
GPT teacher head0.226
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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