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Record W4390749613 · doi:10.1038/s43247-023-01179-5

Millennial-scale variations in Arctic sea ice are recorded in sedimentary ancient DNA of the microalga Polarella glacialis

2024· article· en· W4390749613 on OpenAlex
Sara Harðardóttir, James Haile, Jessica Louise Ray, Audrey Limoges, Nicolas Van Nieuwenhove, Catherine Lalande, Pierre‐Luc Grondin, Rebecca Jackson, Katrine Sandnes Skaar, Maija Heikkilä, Jørgen Berge, Nina Lundholm, Guillaume Massé, Søren Rysgaard, Marit‐Solveig Seidenkrantz, Stijn De Schepper, Eline D. Lorenzen, Connie Lovejoy, Sofia Ribeiro

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCommunications Earth & Environment · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversity of ManitobaMakivik CorporationUniversity of New BrunswickUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaInstitut Polaire Français Paul Emile VictorCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesAgence Nationale de la RechercheCanada Excellence Research Chairs, Government of CanadaUniversité LavalArcticNetDanmarks Frie ForskningsfondVillum FondenEuropean CommissionHorizon 2020 Framework Programme
KeywordsArcticScale (ratio)Sea iceOceanographyThe arcticGeologySedimentary rockArctic ice packPhysical geographyPaleontologyGeographyCartography

Abstract

fetched live from OpenAlex

Abstract Sea ice is a critical component of the Earth’s Climate System and a unique habitat. Sea-ice changes prior to the satellite era are poorly documented, and proxy methods are needed to constrain its past variability. Here, we demonstrate the potential of sedimentary DNA from Polarella glacialis , a sea-ice microalga, for tracing past sea-ice conditions. We quantified P. glacialis DNA (targeting the nuclear ribosomal ITS1 region) in Arctic marine and fjord surface sediments and a sediment core from northern Baffin Bay spanning 12,000 years. Sea ice and sediment trap samples confirmed that cysts of P. glacialis are common in first-year sea ice and sinking particulate matter following sea-ice melt. Its detection is more efficient with our molecular approach than standard micropaleontological methods. Given that the species inhabits coastal and marine environments in the Arctic and Antarctic, P. glacialis DNA has the potential to become a useful tool for circum-polar sea-ice reconstructions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.214
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