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Record W4368370339 · doi:10.1177/15501906231167574

Arctic Specimens in the Zoological Collections at the Natural History Museum, University of Oslo, Norway (NHMO)

2023· article· en· W4368370339 on OpenAlexaboutno aff
Lars Erik Johannessen, Arild Johnsen, Thore Koppetsch, Jan T. Lifjeld, Michael Matschiner, Geir Søli, Kjetil Lysne Voje

Bibliographic record

VenueCollections A Journal for Museum and Archives Professionals · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticNatural historyArchaeologyFish <Actinopterygii>GeographyTaxonZoologyBiologyFisheryEcologyOceanographyGeology

Abstract

fetched live from OpenAlex

In the NHMO zoological collections, specimens from the Arctic include about 9,000 mammals and 7,100 birds, whereas the Insect Collection holds about 105,000 specimens plus more than hundred jars with unsorted material. The Fish Collection contains approximately 1,400 specimens, while the Herptile Collection (amphibians & reptiles) holds only thirty-one specimens of three taxa. Many of these specimens originate from expeditions to E Greenland, N Canada, Svalbard, Novaya Zemlya, Finnmark, and NE Siberia in the period 1898 to 1966. Furthermore, the DNA Bank has about 5,600 tissue and extracted DNA samples, mostly sampled from wild animals during the last decades but also from specimens in the voucher collections. Most of the Arctic specimens have been digitized and are available in online data portals like GBIF, except for the Insect Collection, where only the type material and about 30 percent of the total specimens are digitized.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.088
Threshold uncertainty score0.270

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0810.027

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 head0.024
GPT teacher head0.237
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCollections A Journal for Museum and Archives ProfessionalsSame topicEnvironmental DNA in Biodiversity StudiesFrench-language works237,207