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Record W2587138462 · doi:10.1139/as-2016-0051

Finnish botanists and mycologists in the Arctic

2017· article· en· W2587138462 on OpenAlexvenueaboutno aff
Henry Väre

Bibliographic record

VenueArctic Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersVedecká Grantová Agentúra MŠVVaŠ SR a SAV
KeywordsHerbariumPeninsulaGeographyArcticKola peninsulaLichenArchaeologyTaxonEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Finnish botanists and mycologists have studied Arctic areas and timberline regions since the beginning of the 18th century. Most expeditions to the Kola Peninsula were made between 1800 and 1917 and until 1945 to Lapponia petsamoënsis on the western rim of the Kola Peninsula. Since those years, these areas have been part of the Soviet Union or Russia. Svalbard and Newfoundland and Labrador have been studied repeatedly as well, Svalbard since the 1860s and Newfoundland and Labrador since the 1930s. This article focuses on Finnish collections. These are deposited in the herbaria of Helsinki, Turku, and Oulu universities, except materials from the Nordenskiöld expeditions, which were mainly deposited in Stockholm. Concerning the Kola Peninsula, collections at Helsinki are the most extensive. The exact number of specimens is not known, but by rough estimation, the number is about 60 000, with an additional 110 000 observations included in the database. These expeditions have provided material to describe 305 new taxa to science, viz. 47 algae, 78 bryophytes, 25 fungi, 136 lichens, and 19 vascular plants. This number is an underestimate, as many new species have been described in several separate taxonomic articles. At least 63 persons have contributed to making these collections to Finnish herbaria. Of those, 52 are of Finnish nationality.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.054
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.264
Teacher spread0.235 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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