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Record W4392757996 · doi:10.5194/egusphere-egu24-14690

SVALCLIME – Targeting deep-time Arctic climate archives of Svalbard

2024· preprint· en· W4392757996 on OpenAlexaff
Denise K. Kulhanek, Valentin Zuchuat, Morgan T. Jones, Jiří Bárta, William J. Foster, Wolfram Geissler, Sten‐Andreas Grundvåg, Henning Lorenz, Sverre Planke, Kim Senger, Grace Shepherd, Kasia K. Śliwińska, Aleksandra Smyrak‐Sikora, Lidya G. Tarhan, Madeleine L. Vickers, Maximilian Weber, Weimu Xu, Daniel Kramer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsArcticThe arcticClimatologyEnvironmental scienceOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

The Svalbard archipelago, located in the Norwegian High Arctic, preserves more than 650 million years of near-continuous sedimentary rock records spanning from the Neoproterozoic to the Cenozoic. The polar paleogeographic location of Svalbard in the late Mesozoic and the Cenozoic makes sites in Svalbard unique amongst well-studied temporally equivalent successions from lower paleolatitudes, allowing investigation of the polar amplification climatic effect over geological time. The sedimentary record of Svalbard has been largely controlled by northward drift of constituent geological provinces throughout much of the Phanerozoic and evolving tectono-stratigraphic environments including the influence of several Large Igneous Provinces (LIPs) and global climate fluctuations. The SVALCLIME initiative aims to systematically drill and core the sedimentary successions in Svalbard. Two sub-projects currently being evaluated by the ICDP materialized from an international workshop held in Longyearbyen in October 2022. The first is a full ICDP proposal focused on hyperthermals from the Permian to Paleogene (SVALCLIME P2P) and an ICDP-IODP Land to Sea preproposal on hothouse to coldhouse transitions in the late Paleozoic and across the Eocene–Oligocene transition (SVALCLIME Hot2Cold).The SVALCLIME P2P project aims to investigate the high-resolution Arctic paleoclimate record from 255 to 45 Ma onshore Svalbard that encompasses several Mesozoic and Cenozoic hyperthermal events and the near-field impacts of three LIPs (the Siberian Traps, the High Arctic LIP and the North Atlantic Igneous Province). Our focus will also be on the deep biosphere to uncover the relationship between mineral substrates and taxonomic and metabolic diversity of intraterrestrial microbiomes. We propose to core seven boreholes at three locations (Nordenskiöldfjellet, Botneheia and Kropotkinfjellet), with a cumulative total cored length of ~3.4 km. The SVALCLIME Hot2Cold project aims to address global transitions from hothouse to icehouse conditions during the late Paleozoic and the Eocene to Oligocene. In the preproposal we identify suitable drill sites both onshore and offshore to characterize these periods. The Forlandsundet Graben in western Spitsbergen offers an opportunity to decipher the evolution of the Fram Strait and its impact on global oceanographic circulation during the Eocene–Oligocene transition. The Upper Carboniferous to Early Permian syn and post-rift deposits of the Billefjorden Trough will be targeted to investigate >130 cyclothems originating from glacioeustatic sea level fluctuations.In this contribution, we outline the background and motivation of the SVALCLIME initiative and present the scientific objectives and the proposed drill sites.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0030.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.235
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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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