Six linear regression models for the magnetic susceptibility of sediment core GeoB18530-1

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Main Authors: von Dobeneck, Tilo, Bukar, Shettima
Format: Dataset Open Access
Language:en
Published: PANGAEA 2025
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author von Dobeneck, Tilo
Bukar, Shettima
author_facet von Dobeneck, Tilo
Bukar, Shettima
collection Datos científicos de ciencias marinas y ambientales
contents Six linear regression estimates of magnetic susceptibility were empirically tested for their ability to predict distinct HLs and ILs signal patterns. As predictors, we used MD magnetite content (IRM 20 mT), magnetic grain size (SIRM/X), dolomite and granite proxies (Ca/Sr and K/Fe), bulk porosity (%), dolomite and granite counts, and counts of the major 13 IRD species. As the obtained numbers and residues demonstrate, the rock magnetic proxies yield the best fits, followed by element ratios and porosity. The count-based predictors are incapable of estimating the older HLs 3-H5a and ILs 4-6 correctly; their regression coefficients also do not conform to the measured susceptibilities of the IRD species.
format Dataset Open Access
id pangaea_https___doi_org_10_1594_PANGAEA_971784
institution PANGAEA
language en
publishDate 2025
publisher PANGAEA
record_format pangaea
spellingShingle Six linear regression models for the magnetic susceptibility of sediment core GeoB18530-1
von Dobeneck, Tilo
Bukar, Shettima
509-1; ArcTrain; Calculated from linear regression; DEPTH, sediment/rock; GC; GeoB18530-1; Geochemistry; grain size distribution; Grand Banks Margin; Gravity corer; Heinrich event; Heinrich events; Ice-Rafted Detritus; Linear regression equation; Linear regression model; Magnetic susceptibility; Maria S. Merian; MSM39; Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic; Residual value; rock magnetism; SE Grand Banks Slope
Six linear regression estimates of magnetic susceptibility were empirically tested for their ability to predict distinct HLs and ILs signal patterns. As predictors, we used MD magnetite content (IRM 20 mT), magnetic grain size (SIRM/X), dolomite and granite proxies (Ca/Sr and K/Fe), bulk porosity (%), dolomite and granite counts, and counts of the major 13 IRD species. As the obtained numbers and residues demonstrate, the rock magnetic proxies yield the best fits, followed by element ratios and porosity. The count-based predictors are incapable of estimating the older HLs 3-H5a and ILs 4-6 correctly; their regression coefficients also do not conform to the measured susceptibilities of the IRD species.
title Six linear regression models for the magnetic susceptibility of sediment core GeoB18530-1
topic 509-1; ArcTrain; Calculated from linear regression; DEPTH, sediment/rock; GC; GeoB18530-1; Geochemistry; grain size distribution; Grand Banks Margin; Gravity corer; Heinrich event; Heinrich events; Ice-Rafted Detritus; Linear regression equation; Linear regression model; Magnetic susceptibility; Maria S. Merian; MSM39; Processes and impacts of climate change in the North Atlantic Ocean and the Canadian Arctic; Residual value; rock magnetism; SE Grand Banks Slope
url https://doi.org/10.1594/PANGAEA.971784