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Record W2338721009

Natural radionuclide studies during the GEOTRACES section with Polarstern in the Arctic, Summer 2015

2016· article· en· W2338721009 on OpenAlexaboutno aff
Michiel M Rutgers van der Loeff, Ole Valk, Montserrat Roca‐Martí, Micha J.A. Rijkenberg, Núria Casacuberta, Lars‐Éric Heimbürger‐Boavida, Heather Reader

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsGeotracesOceanographyArcticGeologyRadionuclideEnvironmental scienceSeawater
DOInot available

Abstract

fetched live from OpenAlex

In the summer of 2015 a coordinated pan-arctic GEOTRACES study was executed by the Canadian CCGS Amundsen, the US CGC Healy and the German RV Polarstern. For intercalibration purposes, three cross-over stations were visited, one of them at the North Pole. The Polarstern expedition visited the Nansen, Amundsen and Mendeleev basins. On sections across these basins and the Gakkel and Lomonosov Ridge we collected samples for the full set of GEOTRACES key parameters and many additional analyses. The team of natural radionuclides took samples for U-series nuclides. During earlier work in the central Arctic with Polarstern we have quantified export production with 234Th, studied the interaction between scavenging and deep water ventilation using 230Th and 231Pa, and investigated the shelf-basin exchange with radium isotopes. I will give an overview of these results obtained on earlier expeditions, mention first results of the 2015 expedition, and discuss how these tracers can help us to observe changes in deep water circulation and particle flux that may be related to Arctic Oscillation or caused by sea ice retreat.

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 score0.157
Threshold uncertainty score0.313

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.242
Teacher spread0.229 · 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
Published2016
Admission routes1
Has abstractyes

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