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Record W4232330240 · doi:10.1139/as-2017-0038

Arctic Museum collections: Documenting and understanding changes in biological and cultural diversity through time and space

2017· article· en· W4232330240 on OpenAlexvenueno aff

Bibliographic record

VenueArctic Science · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)ArcticThe arcticSpace (punctuation)GeographyArchaeologyAnthropologyEcologyComputer scienceSociologyBiologyOceanographyGeology

Abstract

fetched live from OpenAlex

Arctic Museum collections: Documenting and understanding changes in biological and cultural diversity through time and spaceThe role of museums and herbaria in biodiversity and cultural synthesis efforts in the Arctic is to preserve the physical and cultural specimens and to advance scientific knowledge by improving access to digitized information.The information associated with these collections, such as geographic, cultural, environmental, phenology, and other information about associated organisms, collector field notes, and tissues and molecular data extracted from the specimens is an invaluable resource providing the baseline from which to further biodiversity research and provide critical information about existing gaps in our knowledge of life in the Arctic.Effective management and conservation of high-latitude biological and cultural diversity in the face of unprecedented rates of climate change requires information on past and current patterns of diversity and their evolution.This special issue of Arctic Science presents results from a workshop entitled "Arctic Museum Collections: Documenting and understanding changes in biological and cultural diversity through time and space" held during Arctic Science Summit Week in March 2016 at the University of Alaska Fairbanks.The workshop brought together scientists from many Arctic nations and focused on current informatics infrastructure, developing large networks of Arctic collections collaborators, and engaging new members and their students in many issues relevant to the Arctic and Subarctic.Lewis et al. review the status of knowledge of genetic diversity and evolutionary history for bryophyte taxa as it relates to shifting species ranges and colonization of new habitats.The University of Alaska Museum is a leader in Arctic and Subarctic collections and their digitization (with our multicollection database Arctos, arctosdb.org).Sikes et al. review rapid digitization efforts in entomological collections in the Arctic and highlight the open-access, online presence of the University of Alaska Museum's rapidly growing entomological collection.To answer relevant questions on the impact of change on high-latitude biological and cultural diversity, we need to synthesize and continue to generate baseline information on Arctic and Subarctic systems.Winker and Withrow show the inadequacy of most specimen collections to the task at hand of facilitating biodiversity assessment and conservation using the bird collections at the University of Alaska Museum as an example.They argue that we need to work collectively to fill temporal, spatial, and taxonomic gaps so we can develop and wield the science that will make us better stewards of Arctic environments.Several contributions in this special volume underscore the international, collaborative scope of Arctic research, including a detailed account of the historical exploration and specimen contributions from Finnish botanists and mycologists by Väre, or the description of baseline data acquisition on plant communities on Greenland accomplished through the Greenland Botanical Survey and subsequent field campaigns, the specimens from which are

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.999

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 studies0.0240.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.179
GPT teacher head0.402
Teacher spread0.224 · 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.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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