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Record W2299259889 · doi:10.5194/bg-13-4205-2016

Sedimentary response to sea ice and atmospheric variability over theinstrumental period off Adélie Land, East Antarctica

2016· article· en· W2299259889 on OpenAlexafffund
Philippine Campagne, Xavier Crosta, Sabine Schmidt, Marie Noëlle Houssais, Olivier Ther, Guillaume Massé

Bibliographic record

VenueBiogeosciences · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsTakuvik Joint International LaboratoryUniversité Laval
FundersEuropean Social FundSeventh Framework ProgrammeInstitut Polaire Français Paul Emile VictorFonds de recherche du Québec – Nature et technologiesCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsDiatomSedimentary rockOceanographySea iceGeologyContinental shelfSedimentPeriod (music)Biogenic silicaIce corePhysical geographyEnvironmental sciencePaleontologyGeography

Abstract

fetched live from OpenAlex

Abstract. Diatoms account for a large proportion of primary productivity in Antarctic coastal and continental shelf zones. Diatoms, which have been used for a long time to infer past sea surface conditions in the Southern Ocean, have recently been associated with diatom-specific biomarkers (highly branched isoprenoids, HBI). Our study is one of the few sedimentary research projects on diatom ecology and associated biomarkers in the Antarctic seasonal sea ice zone. To date, the Adélie Land region has received little attention, despite evidence for the presence of high accumulation of laminated sediment, allowing for finer climate reconstructions and sedimentary process studies. Here we provide a sequence of seasonally to annually laminated diatomaceous sediment from a 72.5 cm interface core retrieved on the continental shelf off Adélie Land, covering the 1970–2010 CE period. Investigations through statistical analyses of diatom communities, diatom-specific biomarkers and major element abundances document the relationships between these proxies at an unprecedented resolution. Additionally, comparison of sedimentary records to meteorological data monitored by automatic weather station and satellite derived sea ice concentrations help to refine the relationships between our proxies and environmental conditions over the last decades. Our results suggest a coupled interaction of the atmospheric and sea surface variability on sea ice seasonality, which acts as the proximal forcing of siliceous productivity at that scale.

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)0.002
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 score0.008
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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

Citations28
Published2016
Admission routes2
Has abstractyes

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