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Record W4415820944 · doi:10.19189/001c.128503

Communities of Larger Fungi of Ombrotrophic Bogs in West Siberia

2014· article· en· W4415820944 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMires and Peat · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsStantec (Canada)
FundersLomonosov Moscow State University
KeywordsBogOmbrotrophicTaxonSpecies richnessHabitatBorealTaiga

Abstract

fetched live from OpenAlex

Bogs are common ecosystems in the Taiga of West Siberia. Little is known about mycological diversity in these important ecosystems. This article summarises the results of a two-year study of the macrofungi in two bogs near the town of Khanty-Mansiysk. Sporocarps were collected in 20 plots (about 300 m 2 ) established in Mukhrino Bog as well as during random walks in Mukhrino Bog and Chistoe Bog in the late summer–autumn of 2012 and 2013. The plots were established in two common bog habitats representing the Ledo-Sphagnetum fusci (LS) and Scheuchzerio palustris-Sphagnetum cuspidati (SS) plant community associations. A total of 59 distinct fungal taxa were collected from the two bogs, with the LS association having a higher species richness and diversity than the SS association (50 taxa vs. 16 taxa and 30–40 taxa per 1000 m_2_ vs. 6–10 taxa per 1000 m_2_, respectively). Each of the two plant community associations has its own characteristic fungal taxa, with the LS association having 13 characteristic taxa and the SS association having five. Nearly two thirds of the fungal taxa are saprotrophic, mainly of Sphagnum spp., while others are mycorrhizal, mainly with Pinus spp. Most taxa were collected fewer than ten times during the study period and, hence, are considered rare and may need to be recognised for conservation programmes in this region.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.207
Teacher spread0.199 · 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