Supplemental Material: Stratigraphy of the Eocene–Oligocene Titus Canyon Formation, Death Valley, California, and Eocene extensional tectonism in the Basin and Range

2021 ◽  
Author(s):  
N. Midttun ◽  
et al.
Keyword(s):  
Detrital Zircon ◽  
Large Scale ◽  
Analytical Data ◽  
Basin And Range ◽  
Death Valley ◽  
Data Table ◽  
Additional Explanation

<div>Text: Additional explanation of the methods used to recalculate the Ar/Ar ages of Gutenkunst (2006), Saylor and Hodges (1994), and Saylor (1991). Figure S1: Analytical plots recalculated from <sup>40</sup>Ar/<sup>39</sup>Ar data originally produced by Gutenkunst (2006). Figure S2: Scans of a large scale map and seven isochron plots for five samples provided by B. Saylor (personal commun., 2015). Table S1: Detrital zircon U-Pb analytical data. Table S2: Zircon (U‐Th)/He analytical data. Table S3: Analytical data for <sup>40</sup>Ar/<sup>39</sup>Ar ages of Gutenkunst (2006).<br></div>

scholarly journals Supplemental Material: Stratigraphy of the Eocene–Oligocene Titus Canyon Formation, Death Valley, California, and Eocene extensional tectonism in the Basin and Range

2021 ◽  
Author(s):  
N. Midttun ◽  
et al.
Keyword(s):  
Detrital Zircon ◽  
Large Scale ◽  
Analytical Data ◽  
Basin And Range ◽  
Death Valley ◽  
Data Table ◽  
Additional Explanation

<div>Text: Additional explanation of the methods used to recalculate the Ar/Ar ages of Gutenkunst (2006), Saylor and Hodges (1994), and Saylor (1991). Figure S1: Analytical plots recalculated from <sup>40</sup>Ar/<sup>39</sup>Ar data originally produced by Gutenkunst (2006). Figure S2: Scans of a large scale map and seven isochron plots for five samples provided by B. Saylor (personal commun., 2015). Table S1: Detrital zircon U-Pb analytical data. Table S2: Zircon (U‐Th)/He analytical data. Table S3: Analytical data for <sup>40</sup>Ar/<sup>39</sup>Ar ages of Gutenkunst (2006).<br></div>

scholarly journals Supplemental Material: Stratigraphy of the Eocene–Oligocene Titus Canyon Formation, Death Valley, California, and Eocene extensional tectonism in the Basin and Range

2022 ◽  
Author(s):  
N. Midttun ◽  
et al.
Keyword(s):  
Detrital Zircon ◽  
Large Scale ◽  
Analytical Data ◽  
Basin And Range ◽  
Death Valley ◽  
Data Table ◽  
Additional Explanation

<div>Text: Additional explanation of the methods used to recalculate the Ar/Ar ages of Gutenkunst (2006), Saylor and Hodges (1994), and Saylor (1991). Figure S1: Analytical plots recalculated from <sup>40</sup>Ar/<sup>39</sup>Ar data originally produced by Gutenkunst (2006). Figure S2: Scans of a large scale map and seven isochron plots for five samples provided by B. Saylor (personal commun., 2015). Table S1: Detrital zircon U-Pb analytical data. Table S2: Zircon (U‐Th)/He analytical data. Table S3: Analytical data for <sup>40</sup>Ar/<sup>39</sup>Ar ages of Gutenkunst (2006).<br></div>

scholarly journals Stratigraphy of the Eocene–Oligocene Titus Canyon Formation, Death Valley, California, and Eocene extensional tectonism in the Basin and Range

Geosphere ◽  
2021 ◽  
Author(s):  
Nikolas Midttun ◽  
Nathan A. Niemi ◽  
Bianca Gallina
Keyword(s):  
Detrital Zircon ◽  
Convergence Rates ◽  
Plate Boundary ◽  
Basin And Range ◽  
Late Eocene ◽  
Death Valley ◽  
Central Basin ◽  
Geologic Mapping ◽  
Extensional Basin ◽  
Stress Changes

Geologic mapping, measured sections, and geochronologic data elucidate the tectono-stratigraphic development of the Titus Canyon extensional basin in Death Valley, California, and provide new constraints on the age of the Titus Canyon Formation, one of the earliest syn-extensional deposits in the central Basin and Range. Detrital zircon maximum depositional ages (MDAs) and compiled 40Ar/39Ar ages indicate that the Titus Canyon Formation spans 40(?)–30 Ma, consistent with an inferred Duchesnean age for a unique assemblage of mammalian fossils in the lower part of the formation. The Titus Canyon Formation preserves a shift in depositional environment from fluvial to lacustrine at ca. 35 Ma, which along with a change in detrital zircon provenance may reflect both the onset of local extensional tectonism and climatic changes at the Eocene–Oligocene boundary. Our data establish the Titus Canyon basin as the southernmost basin in a system of late Eocene extensional basins that formed along the axis of the Sevier orogenic belt. The distribution of lacustrine deposits in these Eocene basins defines the extent of a low-relief orogenic plateau (Nevadaplano) that occupied eastern Nevada at least through Eocene time. As such, the age and character of Titus Canyon Formation implies that the Nevadaplano extended into the central Basin and Range, ~200 km farther south than previously recognized. Development of the Titus Canyon extensional basin precedes local Farallon slab removal by ca. 20 Ma, implying that other mechanisms, such as plate boundary stress changes due to decreased convergence rates in Eocene time, are a more likely trigger for early extension in the central Basin and Range.

Caledonian terrane amalgamation of Svalbard: detrital zircon provenance of Mesoproterozoic to Carboniferous strata from Oscar II Land, western Spitsbergen

2013 ◽  
Vol 150 (6) ◽  
pp. 1103-1126 ◽  
Author(s):  
DETA GASSER ◽  
ARILD ANDRESEN
Keyword(s):  
Detrital Zircon ◽  
Large Scale ◽  
Strike Slip ◽  
Western Coast ◽  
Zircon Age ◽  
The North ◽  
Tectonic History ◽  
Icp Ms ◽  
Depositional Age ◽  
Sveconorwegian Orogen

AbstractThe tectonic origin of pre-Devonian rocks of Svalbard has long been a matter of debate. In particular, the origin and assemblage of pre-Devonian rocks of western Spitsbergen, including a blueschist-eclogite complex in Oscar II Land, are enigmatic. We present detrital zircon U–Pb LA-ICP-MS data from six Mesoproterozoic to Carboniferous samples and one U–Pb TIMS zircon age from an orthogneiss from Oscar II Land in order to discuss tectonic models for this region. Variable proportions of Palaeo- to Neoproterozoic detritus dominate the metasedimentary samples. The orthogneiss has an intrusion age of 927 ± 3 Ma. Comparison with detrital zircon age spectra from other units of similar depositional age within the North Atlantic region indicates that Oscar II Land experienced the following tectonic history: (1) the latest Mesoproterozoic sequence was part of a successor basin which originated close to the Grenvillian–Sveconorwegian orogen, and which was intruded byc. 980–920 Ma plutons; (2) the Neoproterozoic sediments were deposited in a large-scale basin which stretched along the Baltoscandian margin; (3) the eclogite-blueschist complex and the overlying Ordovician–Silurian sediments probably formed to the north of the Grampian/Taconian arc; (4) strike-slip movements assembled the western coast of Spitsbergen outside of, and prior to, the main Scandian collision; and (5) the remaining parts of Svalbard were assembled by strike-slip movements during the Devonian. Our study confirms previous models of complex Caledonian terrane amalgamation with contrasting tectonic histories for the different pre-Devonian terranes of Svalbard and particularly highlights the non-Laurentian origin of Oscar II Land.

scholarly journals The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets

2019 ◽  
Vol 35 (24) ◽  
pp. 5359-5360 ◽  
Author(s):  
Caroline J Sands ◽  
Arnaud M Wolfer ◽  
Gonçalo D S Correia ◽  
Noureddin Sadawi ◽  
Arfan Ahmed ◽  
...  
Keyword(s):  
Quality Control ◽  
Statistical Analysis ◽  
Metabolic Profiling ◽  
Large Scale ◽  
Analytical Data ◽  
Processing Quality ◽  
Metabolic Phenotyping ◽  
Python Package

Abstract Summary As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons. The nPYc-Toolbox provides software for the import, pre-processing, QC and visualization of metabolic phenotyping datasets, either interactively, or in automated pipelines. Availability and implementation The nPYc-Toolbox is implemented in Python, and is freely available from the Python package index https://pypi.org/project/nPYc/, source is available at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation can be found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials at https://github.com/phenomecentre/nPYc-toolbox-tutorials.

Sample Quality Criteria

2015 ◽  
Vol 98 (2) ◽  
pp. 265-268 ◽  
Author(s):  
Charles A Ramsey ◽  
Claas Wagner
Keyword(s):  
Confidence Level ◽  
Large Scale ◽  
Analytical Data ◽  
Quality Criteria ◽  
Small Scale ◽  
Sampling Effort ◽  
Sample Collection ◽  
Representative Sampling ◽  
Sample Quality ◽  
Incorrect Decision

Abstract The concept of Sample Quality Criteria (SQC) is the initial step in the scientific approach to representative sampling. It includes the establishment of sampling objectives, Decision Unit (DU), and confidence. Once fully defined, these criteria serve as input, in addition to material properties, to the Theory of Sampling for developing a representative sampling protocol. The first component of the SQC establishes these questions: What is the analyte(s) of concern? What is the concentration level of interest of the analyte(s)? How will inference(s) be made from the analytical data to the DU? The second component ofthe SQC establishes the DU, i.e., the scale at whichdecisions are to be made. On a large scale, a DU could be a ship or rail car; examples for small-scale DUs are individual beans, seeds, or kernels. A well-defined DU is critical because it defines the spatialand temporal boundaries of sample collection. SQC are not limited to a single DU; they can also include multiple DUs. The third SQC component, the confidence, establishes the desired probability that a correct inference (decision) can be made. The confidence level should typically correlate to the potential consequences of an incorrect decision (e.g., health or economic). The magnitude of combined errors in the sampling, sample processing and analytical protocols determines the likelihood of an incorrect decision. Thus, controlling error to a greater extent increases the probability of a correct decision. The required confidence level directly affects the sampling effort and QC measures.

scholarly journals Supplemental Material: Tectonic evolution of the central California margin as reflected by detrital zircon composition in the Mount Diablo region

2021 ◽  
Author(s):  
Jared T. Gooley ◽  
et al.
Keyword(s):  
Sample Preparation ◽  
Detrital Zircon ◽  
Analytical Methods ◽  
Tectonic Evolution ◽  
Data Sources ◽  
Central California ◽  
Data Table ◽  
Geologic Map ◽  
Map Data

Appendix S1: Geologic map data sources; Appendix S2: Sample preparation and analytical methods; Table S1: U-Th-Pb data; Table S2: U-Pb age components.

scholarly journals Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

2018 ◽  
Vol 5 (1) ◽  
pp. 24-34
Author(s):  
I. P. Bangov ◽  
M. Moskovkina ◽  
B. P. Stojanov
Keyword(s):  
Similarity Search ◽  
Large Scale ◽  
Analytical Data ◽  
Analytical Laboratory ◽  
Statistical Process ◽  
White Wines ◽  
Laboratory Parameters ◽  
Individual Laboratory ◽  
Individual Cluster

Abstract This study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine’s quality in each individual cluster was carried out according to individual laboratory parameters.

scholarly journals Supplemental Material: Dating lacustrine carbonate strata with detrital zircon U-Pb geochronology

2020 ◽  
Author(s):  
Emily Finzel ◽  
Justin Rosenblume
Keyword(s):  
Detrital Zircon ◽  
Analytical Data ◽  
Lacustrine Carbonate

Detrital zircon U-Pb analytical data.<br>

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