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Record W7018941611

Ein Roentgendiffraktionsansatz : die Mineralzusammensetzung als Herrkunftsindikator von Sedimenten im Arktischen Ozean

2016· dissertation· en· W7018941611 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMedia (https://www.suub.uni-bremen.de/) · 2016
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsArcticProvenanceSedimentClimate changePaleoceanographyThe arcticPaleoclimatologyDolomite
DOInot available

Abstract

fetched live from OpenAlex

Paleoclimate research and climate models demonstrate that the Arctic is very sensitive to climate change and also plays a key role in driving and amplifying global climate variability and sea-level change. Study of the late Quaternary paleoceanography in the Arctic Ocean is of great importance to understand the glacial-interglacial climate changes. As the sediment in the central Arctic Ocean is mostly transported by iceberg and sea-ice, provenance studies can be used to infer the ice-sheet history and the surface circulation pattern. Bulk mineral assemblages are one of the proxies that can be used to identify the source areas of the Arctic sediments. The main aim of this thesis is to study in detail the quantitative X-Ray Diffraction (qXRD) software package RockJock which is used to obtain the bulk mineral assemblages result and the comparison of the two qXRD software packages RockJock and QUAX. In Chapter 4, three different sets of artificial mixtures are used to access the accuracy of RockJock, and the possible sources of errors are proposed. The comparison of RockJock and QUAX is based on the surface sediment samples retrieved from the Siberian shelf seas as well as the central Arctic Ocean. Quartz, feldspars, calcite, dolomite, and the sum of clay minerals show fairly good correlations, while the differences of individual clay minerals are high. In Chapter 5, surface sediment samples, which are used in Chapter 4, were analyzed using RockJock to test the possibility to use bulk mineral assemblages as provenance indicator. It shows that the combination of quartz, Qz/Fsp, dolomite and kaolinite can be used to identify source areas. Sediment input from the Canadian Arctic is generally characterized by high dolomite and Qz/Fsp values. Sediment input from the Eurasian Arctic shelf seas is generally characterized by low dolomite, Qz/Fsp, kaolinite values and high quartz values. Although the contents of amphibole are mostly too small to be quantified, the occurrence of amphibole might be an indicator of sediments from the Siberian shelf seas. In Chapter 6, three sediment cores selected from a transect across the Mendeleev Ridge were used in this thesis to study the provenance of terrigenous sediments from the Central Arctic in order to study the ice sheet history. It shows that the provenance of sediments deposited on the Makarov Basin side of the Mendeleev Ridge is different from that deposited on the Canada Basin side of the Mendeleev Ridge. The IRD events of MIS16, 12, 10, 8 are characterized by high dolomite contents, high quartz/feldspar ratios and low plagioclase contents and may suggest IRD input from the Canadian Archipelago. The IRD events that occur in MIS6, are characterized by high quartz and low dolomite contents, which indicates IRD from the Eurasian sources.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.010

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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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