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66 results for βGeochemical dataβ
Shuttle Radar Topography Mission digital elevation models, data points, radiocarbon dates, and geochemical data for the Rub' al Khali Desert
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Machine learning based on whole-rock geochemical data: An indication for the porphyry Cu-Au deposits in Central Asian Orogenic Belt
<div> <h2>Introduction</h2> </div> <p>Welcome to the PorphyryAuML project! This repository is dedicated to exploring the mechanism of gold (Au) enrichment in porphyry systems within the Central Asian Orogenic Belt using machine learning. We apply models like XGBoost and Random Forest to analyze whole-rock geochemical data, aiming to classify porphyry deposit types and highlight key geochemical indicators.</p> <div> <h2>Key Features π</h2> </div> <ul> <li><strong>Principal Component Analysis (PCA):</strong> Reduce dimensionality to discover the most significant variables.</li> <li><strong>Machine Learning Models:</strong> Utilize XGBoost and Random Forest for robust classification.</li> <li><strong>Feature Importance Analysis:</strong> Identify crucial geochemical markers for Au presence and quantity.</li> <li><strong>Visualization:</strong> Detailed plots to illustrate model outcomes and geochemical patterns.</li> </ul> <div> <h2>Data π</h2> </div> <div> <h3>DATA.xlsx</h3> </div> <p>The <code>DATA.xlsx</code> file contains crucial geochemical data used in our analysis, organized across three sheets:</p> <ul> <li><strong>group1</strong>: Represents the Cu-Au (Copper-Gold) porphyry deposits. This sheet contains all relevant geochemical markers and measurements specific to this group.</li> <li><strong>group2</strong>: Corresponds to Cu(-Au±Mo) (Copper with minor Gold and possibly Molybdenum) porphyry deposits. It includes a detailed set of data focusing on the variations and characteristics of these mixed element deposits.</li> <li><strong>group3</strong>: Contains data related to Cu-Mo (Copper-Molybdenum) porphyry deposits, focusing on the distinct geochemical profiles that typify these deposits.</li> </ul> <p>Each sheet is named to reflect the group it represents and is vital for our machine learning analysis to classify and predict porphyry deposit types based on their geochemical properties.</p>
Data for "Uncertainty quantification in geochemical mapping: a review and recommendations"
<p>Data for "Uncertainty quantification in geochemical mapping: a review and recommendations".</p>
Geochronological and geochemical data of volcanic deposits of the Central Main Ethiopian Rift
<p>This database represents a collection of geochronological data, geochemistry of bulk rocks and melt inclusions from a large set of samples collected in the framework of two field surveys (2019, 2020) in the Central Main Ethiopian Rift.</p> <p>This dataset provides supporting information to the paper:<br>Franceschini Z., Cioni R., Scaillet S., Prouteau G., Corti G., Sani F., Mondanaro A., Frascerra D., Melaku A.A., Scaillet B., Oppenheimer C., Duval F. (2024) "Pulsatory volcanism in the Main Ethiopian Rift and its environmental consequences", Nature Communications Earth and Environment.</p> <p>The samples have been prepared for the different analyses at the Department of Earth Sciences of the University of Florence. The geochronological analyses building up the dataset have been performed at the Argon facility at the Institut des Sciences de la Terre d'Orléans (ISTO), in France. The analythical methods related to the 40Ar/39Ar analyses are described in detail in the above mentioned paper.<br>The geochemical dataset contains the results of major and trace elements concentrations on whole rock samples (performed at the Service d'Anlayse des Roches et des Mineraux -CNRS - CRPG of Nancy, in France) and major elements and volatile concentrations of melt inclusions belonging to four ignimbrite samples (analysed with an Electron Micro Probe Analyzer housed at the laboratories of the Institut des Sciences de la Terre d'Orléans, in France).</p> <p>These datasets have been performed in the frame of a PhD fellowship (granted to Zara Franceschini) funded by the Università Italo Francese (Bando Vinci 2018, n. C3-1717) and also partially supported by the Italian Ministero dell'Università e della Ricerca (MiUR) through PRIN grant 2017P9AT72.</p>
Geochemical data for protolith classification testing
<p>Global major element geochemical data for igneous and sedimentary rocks. This dataset is used to train via machine learning a classifier for igneous and sedimentary protoliths. It contains the major element chemistry, ilr transformed chemistry, rock type, protolith class, and reference to the original data. Codes to train a protolith classifier and analyze the results are found in the GitHub repository github.com/dhasterok/global_geochemistry/</p>
The coincidence degree between the geochemical behavior of elements and the periodic variation of elements based on geochemical data of C2 coal seam in the Fengfeng mining area of the Handan Coalfield in Hebei, China
<p>In this data-set, based on the geochemical data of C2 coal seam in the Fengfeng mining area of the Handan Coalfield in Hebei (China), where provided ideal coal samples changing continuously from low-rank metamorphic coal to high-rank metamorphic coal, the coincidence degree (or similarity degree) between the geochemical behavior of 57 elements and the periodic variation of elements during the thermal metamorphism process is calculated.</p>
Geochemical data of fine bed-sediment from downstream sediment cores and upstream source sub-catchments in a catchment-wide flood in the Brantian
<b>Description: </b><p>Geochemical datasets were obtained from fieldwork carried out in the Brantian catchment between June 2013 and November 2016 under the hydrology component of the SAFE Project. The project has two key components: (1) Geochemical profiles down historical sediment cores at seven downstream locations organised in a nested hierarchical arrangement; and (2) Geochemical data for sediment deposited by the single extreme high magnitude flood event of 12 September 2016 in all sub-catchment source areas sampled around the Brantian including all downstream sediment core locations referred to in (1) <br>Sample collection and preparation method:<br>Fluvial sediment cores were obtained from seven downstream sites located within a nested hierarchical (dendritic) arrangement with the study catchment outlet draining 377 km2 of the upper Brantian. Core sites 4 and 5 in the west were nested within core site 2; core sites 6 and 7 in the east were nested within core site 3; core sites 2 and 3 were in turn nested within core site 1 at the study catchment outlet. Areas upstream at each drainage hierarchy varied from 30-135km2 (core sites 4-7); 150-200km2 (core sites 2-3) and 377km2 (core site 1).<br>Sediment cores were obtained within the bankfull channel at sites inundated by high-flow events with the progressive accumulation of fine bed-sediment monitored by repeat measurements of surface profile. Pits were dug to create a shelf surface from which to obtain large (200g to 1100g) bulk samples of sediment integrated over depth intervals of 2cm. The shelf technique permits larger samples while depths are absolute and not affected by core liner compression. Core depths ranged from 102 cm to 210 cm.<br>Sediment samples deposited in the high-flow event of 12 September 2016 were obtained using pre-installed surface horizon marker grids. Surface-layer (0-2cm) scrape samples were composited over a 10-20 m2 area. At sites with depths of fresh sediment >2cm small sediment cores representing sediment deposited in that event were obtained using the shelf technique. Field replicates were obtained from the same elevation and at either higher or lower elevation within the channel.<br>All sediment samples were oven-dried at temperatures no higher than 40 C before dry-sieving to obtain the fine-sediment <63um size fraction. Other size fractions were obtained from nested sieve stacks in order to calculate bulk particle size distribution from the entire sample. Samples of dried <63um sediment were thoroughly mixed by hand (not ground) before a sub-sample transferred to a standard 32mm outer-diameter plastic pot pre-fitted with a 3um thick Prolene XRF analytical film window, compacted to 20Nm torque pressure and sealed. Mass (g) and total thickness (mm) of prepared samples were recorded. <br>Geochemical analysis method:<br>Total elemental concentration of each sample (ppm) was measured using a Niton XL3t GOLDD+ 900 Energy-Dispersive X-Ray Fluorescence (ED-XRF) analyser in a laboratory stand with count periods of 180 seconds for 'soils' (Compton scatter) mode (60s in each of three energy band filters: low medium and high). Measurements were also made in 'mining' mode (Fundamental Parameters calibration) using helium purging to obtain concentrations of light elements Mg-S. In both modes, two measurements were obtained for each sample by repositioning the sample window exposed to the XRF beam after the first measurement (position 1 and position 2). <br>ED-XRF analysis returns total elemental concentration (ppm) of elements Mg-U. Measurement error is reported by the Niton XRF in terms of 2sigma (two times standard deviation) for each element. All measurements were higher than limit of detection. Variability between the two measurement positions 1 and 2 reflects geochemical environmental variability in sediment (ie sampling error) and analytical error.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/133"><b>Assessing erosional impacts of logging and conversion to oil palm in the Brantian catchment using sediment fingerprinting and radioisotope dating.</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Doctoral Training Grant, NE/L501827/1)</li><li>British Geomorphological Society (Postgraduate Research Grant)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/2 JLD.3(149))</li><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/2 JLD.5(145))</li><li>Sabah Forestry Department (Research licence 100-14/18/2KLT.29(37))</li><li>Maliau Basin Management Committee (MBMC) (Research licence 2015/29(165))</li><li>Sabah Biodiversity Council (Export licence JKM/MBS.1000-2/3 JLD.2(86))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3402746">here</a></p><p><b>Files: </b>This consists of 1 file: SamHigton_Geochem_fluvial_sediment_data.xlsx</p><p><b>SamHigton_Geochem_fluvial_sediment_data.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Sediment core geochemistry data</b> (described in worksheet Sediment_core_geochem_data)</p><p>Description: XRF analysis data of geochemical composition of sediment from 7 core sites. There is one sample for every 2cm depth interval down each core (with one set of bulk particle size data) and then two separate repeat XRF measurements of each sample.</p><p>Number of fields: 69</p><p>Number of data rows: 947</p><p>Fields: </p><ul><li><b>Core_number</b>: Core number (Field type: id)</li><li><b>Sample_Site</b>: Corresponds to sample site number in the locations tab (Field type: location)</li><li><b>Upstream_Area_km2</b>: Upstream area (Field type: numeric)</li><li><b>Sampling_date</b>: Date sediment sample taken (Field type: date)</li><li><b>Upper_Depth_cm</b>: Upper depth of sample slice relative to the sediment surface; for surface samples this will always be zero (Field type: numeric)</li><li><b>Lower_Depth_cm</b>: Lower depth of each sample slice relative to the sediment surface; in increments of 2cm (Field type: numeric)</li><li><b>BulkPS_<63um_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_63-125um_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_125um-2mm_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_>2mm_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>XRF_sample_mass_g</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>XRF_sample_thick_mm</b>: Mass of XRF sample analysed (Field type: numeric)</li><li><b>EDXRF_measurement_number_1or2</b>: Refers to XRF measurement 1 or 2 - each sample was analysed in two different positions across the sample measurement surface producing two measurements of element concentration and 2SD error for each sample (Field type: categorical)</li><li><b>Mg</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Al</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Si</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>P</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>S</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>K</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ca</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ti</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>V</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Mn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Fe</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ni</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cu</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Zn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>As</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Rb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Zr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cd</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Te</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cs</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ba</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Pb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Th</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>U</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Mg.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Al.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Si.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>P.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>S.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>K.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ca.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ti.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>V.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Mn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Fe.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ni.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cu.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Zn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>As.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Rb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Zr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cd.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Te.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cs.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ba.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Pb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Th.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>U.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li></ul></li><li><p><b>Sept2016 flood geochemical data</b> (described in worksheet Sept2016_flood_geochem_data)</p><p>Description: XRF analysis of geochemical composition of sediment from a single flood event around the Brantian. Most samples have depth of 0-2cm since this represents surface layer material, but at many sites there were also 'mini' cores which is why the depths vary. 28 elements analysed as above and each sample measured twice, with error columns and bulk particle size etc.</p><p>Number of fields: 70</p><p>Number of data rows: 222</p><p>Fields: </p><ul><li><b>Sample_Site</b>: Corresponds to sample site number in the locations tab (Field type: location)</li><li><b>Site_Type</b>: Site Type - U: Upstream site (sample taken at one of the upstream source sites 9 to 29) ; C: Core site (sample at a sediment core site which are only sites numbered 1 to 7); RC: Field replicate from the sediment core site itself; RL: Field replicate at that site but from a relatively lower elevation position; RH: Field replicate at that site but from a relatively higher elevation position) (Field type: categorical)</li><li><b>Upstream_Area_km2</b>: Total drainage area upstream of each sample site (Field type: numeric)</li><li><b>Sampling_date</b>: Date sediment sample taken (Field type: date)</li><li><b>Upper_Depth_cm</b>: Upper depth of sample slice relative to the sediment surface; for surface samples this will always be zero (Field type: numeric)</li><li><b>Lower_Depth_cm</b>: Lower depth of each sample slice relative to the sediment surface; in increments of 2cm (Field type: numeric)</li><li><b>BulkPS_<63um_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_63-125um_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_125um-1mm_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_1mm-2mm_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>BulkPS_>2mm_%</b>: % of bulk particle size distribution obtained by dry sieved mass (Field type: numeric)</li><li><b>XRF_sample_mass_g</b>: Mass of XRF sample analysed (Field type: numeric)</li><li><b>XRF_sample_thick_mm</b>: Thickness of prepared sample for XRF analysis (to nearest 0.5cm) (Field type: numeric)</li><li><b>EDXRF_measurement_number_1or2</b>: Refers to XRF measurement 1 or 2 - each sample was analysed in two different positions across the sample measurement surface producing two measurements of element concentration and 2SD error for each sample (Field type: categorical)</li><li><b>Mg</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Al</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Si</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>P</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>S</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>K</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ca</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ti</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>V</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Mn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Fe</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ni</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cu</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Zn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>As</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Rb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Zr</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cd</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sn</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Sb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Te</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Cs</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Ba</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Pb</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Th</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>U</b>: Total elemental concentration measured by ED-XRF (Energy Dispersive X-Ray Fluorescence) (Field type: numeric)</li><li><b>Mg.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Al.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Si.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>P.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>S.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>K.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ca.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ti.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>V.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Mn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Fe.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ni.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cu.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Zn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>As.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Rb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Zr.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cd.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sn.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Sb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Te.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Cs.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Ba.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Pb.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>Th.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li><li><b>U.Error</b>: Error for each measurement, equal to 2 times standard deviation (2 sigma) (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2013-06-21 to 2019-12-31</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Data from : Geochemical and Documentary Topography of a Medieval Silver Valley
<p>These data are the source of an interdisciplinary investigation (archaeology, geochemistry, history) of a medieval silver and lead production site located in southern France, in the Minier valley (Occitanie, Aveyron, Le-Viala-du-Tarn). In order to identify the production sites, in situ geochemical surveys were carried out using a portable X-ray fluorescence spectrometer and differential GPS, guided on the analysis of medieval archival sources. The cartographic representation of the metal concentrations in the surface horizons shows significant enrichment of zinc and lead in the vicinity of the mines. This first type of enrichment makes it possible to highlight the activities of separation of sphalerite and silver-bearing galena. The galena thus isolated on the hillsides is then transported to the vicinity of watercourses, where it is crushed, washed, and smelted. These secondary activities result in a last type of enrichment in which only lead is found in large quantities. The cross-referencing of the information made it possible to overcome the challenges related to the location of the mineral processing workshops, which were often invisible on the surface. The medieval workshops have been located and a function suggested, outlining the first trends in the spatial and social division of labour and providing a solid corpus for future archaeological excavations. Finally, this study highlights the persistence of significant metal contamination in the soils of a rural valley and encourages the consideration of former mining areas when examining the environmental impact of metal production.</p>
Geochronological and geochemical data for Late Triassic granitic rocks in Central Qiangtang
<p>Supplementary Table 1. Zircon isotopic LA-ICP-MS analyses for the granitoid samples.</p> <p>Supplementary Table 2. Major (wt.%) and trace element (ppm) compositions of the granitoid samples.</p> <p>Supplementary Table 3. Hf isotopes of zircons of the granitoid samples.</p> <p>Supplementary Table 4. Summary of age data for the Late Triassic magmatic rocks and metamorphic rocks in the Central Qiangtang.</p>
Geochemical, timescales data in orthopyroxenes from Kizimen 2010 eruption and database of studies linking diffusion timescales with monitoring signals.
<p>This dataset comprises the geochemical data on whole rock analysis, melt inclusions, residual glasses, magnetites and orthopyroxenes in samples from the 2010 eruption of Kizimen volcano (Kamchatka), as well as the timescales modelled in the orthopyroxenes and a database of studies linking diffusion timescales with monitoring signals, associated with the publication: Ostorero, L., Balcone-Boissard, H., Boudon, G. <em>et al.</em> Correlated petrology and seismicity indicate rapid magma accumulation prior to eruption of Kizimen volcano, Kamchatka. <em>Commun Earth Environ</em> <strong>3</strong>, 290 (2022). https://doi.org/10.1038/s43247-022-00622-3</p> <p> </p>
Mg and Fe isotopes and other geochemical data for Gangdese arc mafic plutonic rocks and trench sediments
<p>These files content unpublished Mg and Fe isotopes and other geochemical data for the Gangdese arc mafic plutonic rocks and trench sediments.</p>
Data set for "Tectonic evolution of the Tibetan Plateau during the late Cretaceous to early Eocene: Insights from geochemical records in the Fenghuoshan Group, Hoh Xil Basin"
<p>The mineral compositions, major and trace element gechemical data for the sediements from Fenghuoshan Group, Hoh Xil Basin.</p>
Wrangell Arc, Alaska (U.S.A.) clast geochemical data - Table S1
<p>Supplemental bulk rock major-trace element geochemical data, 40Ar/39Ar ages, and sample locations for modern river clasts (from Wrangell Arc, Alaska, USA). </p>
Cleveland Shale geochemical data
<p>Supplementary data for Geochemistry, Geophysics, Geosystems publication "<strong>Geochemical and hydrographic evolution of the Late Devonian Appalachian Seaway: Linking sedimentation, redox, and salinity across time and space"</strong>.</p>
Neogloboquadrina pachyderma LA-ICP-MS spectral files and stable isotope data from: Geochemical differences between alive, uncrusted and dead, crusted shells of Neogloboquadrina pachyderma: Implications for paleoreconstruction
<p>Planktic foraminiferal-based trace element-calcium ratios (TE/Ca) are a cornerstone in paleoceanographic reconstructions. While TE-environment calibrations are often established through culturing experiments, shell growth in culture is not always consistent with growth in a natural setting. For example, many species of planktic foraminifera thicken their shell at the end of their life cycle, producing a distinct 'gametogenic' crust. Crust is common in fossil foraminifers, however, shells grown in culture do not often develop a thick crust. Here we investigate potential vital effects associated with the crusting process by comparing the trace element (Mg/Ca, Na/Ca, Ba/Ca, Sr/Ca, Mn/Ca, Zn/Ca) and stable isotope (Ξ΄<sup>13</sup>C, Ξ΄<sup>18</sup>O) composition of alive, fully mature, uncrusted shells to recently deceased, crusted shells of <em>Neogloboquadrina pachyderma</em> collected from the same plankton tows off the Oregon (USA) coast. We find that uncrusted (N = 55) shells yield significantly higher Ba/Ca, Na/Ca, Mn/Ca, and Sr/Ca than crusted (N = 66) shells, and crust calcite records significantly lower TE/Ca values for all elements examined. Isotopic mixing models suggest that the crust calcite accounts for ~40 to 70% of crusted shell volume. Comparison of foraminiferal and seawater isotopes indicate that <em>N. pachyderma</em> lives in the upper 90 m of the water column, and that crust formation occurs slightly deeper than their average living depth habitat. Results highlight the necessity to establish calibrations from crusted shells, as application of calibrations from TE-enriched uncrusted shells may yield attenuated or misleading paleoceanographic reconstructions.</p>
Neogloboquadrina pachyderma LA-ICP-MS spectral files and stable isotope data from: Geochemical differences between alive, uncrusted and dead, crusted shells of Neogloboquadrina pachyderma: Implications for paleoreconstruction
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Data from: A compendium of geochemical information from the Saanich Inlet water column
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Data from: Microstructural and geochemical evidence offers a solution to the cephalopod cameral deposits riddle
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Data from: Geochemical analyses reveal the importance of environmental history for blue carbon sequestration
Coastal habitats including saltmarshes and mangrove forests can accumulate and store significant blue carbon stocks, which may persist for millennia. Despite this implied stability, the distribution and structure of intertidal-supratidal wetlands is known to respond to changes imposed by geomorphic evolution, climatic, sea level and anthropogenic influences. In this study, we reconstruct environmental histories and biogeochemical conditions in four wetlands of similar contemporary vegetation in SE Australia. The objective is to assess the importance of historic factors to contemporary organic carbon (C) stocks and accumulation rates. Results from the four cores β two collected from marine influenced saltmarshes (WAP-M and POR-M) and two from fluvial influenced saltmarshes (WAP-F and POR-F) β highlight different environmental histories and preservation conditions. High C stocks are associated with the presence of a mangrove phase below the contemporary saltmarsh sediments in the POR-M and POR-F cores. 13C NMR analyses show this historic mangrove root C to be remarkably stable in its molecular composition despite its age, consistent with its position in deep sediments. WAP-M and WAP-F cores did not contain mangrove root C, however, significant preservation of char C (up to 46% of C in some depths) in WAP-F reveals the importance of historic catchment processes to this site. Together, these results highlight the importance of integrating historic ecosystem and catchment factors into attempts to upscale C accounting to broader spatial scales.
Dataset for the publication "Neutrophilic Bioleaching of Synthetic Covellite β A Model System Combining Experimental Data and Geochemical Modeling"
<p>This dataset contains data, which were used in preparation of the publication "Neutrophilic Bioleaching of Synthetic Covellite – A Model System Combining Experimental Data and Geochemical Modeling"</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.