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Record W4387045496 · doi:10.1038/s43705-023-00313-w

Arctic bacterial diversity and connectivity in the coastal margin of the Last Ice Area

2023· article· en· W4387045496 on OpenAlexafffundabout
Catherine Girard, Warwick F. Vincent, Alexander I. Culley

Bibliographic record

VenueISME Communications · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of CanadaAUTO21 Network of Centres of ExcellenceGovernment of CanadaArcticNetCanada First Research Excellence FundParks CanadaFonds de recherche du Québec – Nature et technologiesUniversité Laval
KeywordsArcticArctic ice packMargin (machine learning)Diversity (politics)OceanographyThe arcticSea iceGeographyPhysical geographyGeologyEcologyBiologyComputer science

Abstract

fetched live from OpenAlex

Arctic climate change is leading to sea-ice attrition in the Last Ice Area along the northern coast of Canada and Greenland, but less attention has been given to the associated land-based ecosystems. Here we evaluated bacterial community structure in a hydrologically coupled cryo-ecosystem in the region: Thores Glacier, proglacial Thores Lake, and its outlet to the sea. Deep amplicon sequencing revealed that Polaromonas was ubiquitous, but differed genetically among diverse niches. Surface glacier-ice was dominated by Cyanobacteria, while the perennially ice-capped, well-mixed water column of Thores Lake had a unique assemblage of Chloroflexi, Actinobacteriota, and Planctomycetota. Species richness increased downstream, but glacier microbes were little detected in the lake, suggesting strong taxonomic sorting. Ongoing climate change and the retreat of Thores Glacier would lead to complete drainage and loss of the lake microbial ecosystem, indicating the extreme vulnerability of diverse cryohabitats and unique microbiomes in the Last Ice coastal margin.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.038
GPT teacher head0.239
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 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

Citations11
Published2023
Admission routes3
Has abstractyes

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