cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7sf2tcv
title: Minisparker seismic-reflection data collected offshore of San Diego and Los Angeles Counties, southern California, from 2011-06-08 to 2011-06-22 (USGS field activity S-7-11-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2011 to collect information on active offshore faults. The survey area is offshore southern California between Long Beach and San Diego. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker and an Edgetech 512 chirp subbottom profiler. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location and equipment type.
DOI: 10.5066/f7vd6wmm
title: Chirp seismic-reflection data collected between Oceanside and La Jolla, offshore of southern California, from 2010-06-01 to 2010-06-12 (USGS field activity S-12-10-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2010 to collect information on active offshore faults. The survey is area is offshore southern California between Oceanside and La Jolla. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using an EdgeTech 512 chirp subbottom profiler. Subbottom acoustic penetration spanned tens to about 50 meters, variable by location.
DOI: 10.5066/f7x63k3k
title: Chirp seismic-reflection data collected offshore of San Diego and Los Angeles Counties, southern California, from 2011-06-08 to 2011-06-22 (USGS field activity S-7-11-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2011 to collect information on active offshore faults. The survey area is offshore southern California between Long Beach and San Diego. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using an EdgeTech 512 subbottom profiler. Subbottom acoustic penetration spanned tens to about 50 meters, variable by location.
DOI: 10.5066/f7ns0s1d
title: Minisparker seismic-reflection data collected between Huntington Beach and San Diego, offshore of southern California, from 2008-04-28 to 2008-05-05 (USGS field activity B-1-08-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2008 to collect information on active offshore faults. The survey area is offshore southern California between Huntington Beach and San Diego. The data were collected aboard the R/V Bold. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.
DOI: 10.5066/f7qn64w8
title: Minisparker seismic-reflection data collected between Oceanside and La Jolla, offshore of southern California, from 2010-06-01 to 2010-06-12 (USGS field activity S-12-10-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2010 to collect information on active offshore faults. The survey area is offshore southern California between Oceanside and La Jolla. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.
DOI: 10.5066/f7f769qg
title: Minisparker seismic-reflection data collected in the San Pedro Basin, offshore of southern California, from 2009-07-06 to 2009-07-10 (USGS field activity S-5-09-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2009 to explore a possible connection between the San Diego Trough Fault and the San Pedro Basin Fault. The survey is in the San Pedro Basin between Santa Catalina Island and San Pedro, California. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.
DOI: 10.5066/f75q4t8f
title: Chirp seismic-reflection data collected in the San Pedro Basin, offshore of southern California, from 2009-07-06 to 2009-07-10 (USGS field activity S-5-09-SC)

description: This dataset includes raw and processed, high-resolution seismic-reflection data collected in 2009 to explore a possible connection between the San Diego Trough Fault and the San Pedro Basin Fault. The survey is in the San Pedro Basin between Santa Catalina Island and San Pedro, California. The data were collected aboard the U.S. Geological Survey R/V Parke Snavely. The seismic-reflection data were acquired, mainly using a SIG 2mille minisparker. Subbottom acoustic penetration spanned tens to several hundreds of meters, variable by location.
DOI: 10.5066/p993gquo
title: Abiotic sorption of glucose, glutamic acid, hydroxybenzoic acid, and oxalic acid onto amorphous aluminum hydroxide, feldspar, ferrihydrite, and kaolinite

description: Abiotic sorption experiments were conducted with four carbon substrates (glucose, glutamic acid, oxalic acid, para-hydroxybenzoic acid) on four clay minerals (kaolinite, feldspar, ferrihydrite, amorphous aluminum hydroxide) after sterilization by gamma irradiation. The adsorption isotherms were carried across a range of substrate carbon concentrations (0, 20, 100, and 500 mg carbon per L) and pH conditions (approximately 5 ? 9) in a background of 10 mM NaCl for 48 hours. The data release contains measured pH values and carbon concentrations before and after the sorption experiments. The release provides derived values of carbon sorption (e.g., carbon sorbed per mineral surface area) as well as characterization of the minerals (e.g., surface area, x-ray diffraction patterns). Users can calculate the derived values independently with ancillary data in the release (e.g., masses, volumes, surface areas). The file "data_dictionary" provides descriptions, valid ranges, and units for all fields in the data files.
DOI: 10.5281/zenodo.7939076
title: LEVELS OF POLYCYCLIC AROMATIC HYDROCARBON IN THE SOIL AROUND TYPICAL AUTOMOBILE REPAIR WORKSHOPS IN NIGERIA

description: the data was obtained for the levels of Polycyclic Aromatic Hydrocarbon in the soil around typical automobile repair workshops in Nigeria.
DOI: 10.5281/zenodo.7939077
title: LEVELS OF POLYCYCLIC AROMATIC HYDROCARBON IN THE SOIL AROUND TYPICAL AUTOMOBILE REPAIR WORKSHOPS IN NIGERIA

description: the data was obtained for the levels of Polycyclic Aromatic Hydrocarbon in the soil around typical automobile repair workshops in Nigeria.
DOI: 10.5281/zenodo.7943022
title: LEVELS OF POLYCYCLIC AROMATIC HYDROCARBON IN THE SOIL AROUND TYPICAL AUTOMOBILE REPAIR WORKSHOPS IN NIGERIA

description: the data was obtained for the levels of Polycyclic Aromatic Hydrocarbon in the soil around typical automobile repair workshops in Nigeria.
DOI: 10.6084/m9.figshare.22582099.v1
title: Smith-Vidaurre_et_al_2023_IdentityInformationEncoding

description: Please see the README file for an overview of the data made available and detailed descriptions about each file. The README also contains information about funding sources. The code to reproduce our analyses is available in the GitHub repository gsvidaurre/identity-information-post-introduction.
DOI: 10.5281/zenodo.8034833
title: Data from "Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness"

description: This repository contains the data from the paper, "Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness." Relevant URLs: https://hewlettpackard.github.io/trust-ml/ https://github.com/HewlettPackard/trust-ml/ Abstract: We present a novel framework for generating adversarial benchmarks to evaluate the robustness of image classification models. The RLAB framework allows users to customize the types of distortions to be optimally applied to images, which helps address the specific distortions relevant to their deployment. The benchmark can generate datasets at various distortion levels to assess the robustness of different image classifiers. Our results show that the adversarial samples generated by our framework with any of the image classification models, like ResNet-50, Inception-V3, and VGG-16, are effective and transferable to other models causing them to fail. These failures happen even when these models are adversarially retrained using state-of-the-art techniques, demonstrating the generalizability of our adversarial samples. Our framework also allows the creation of adversarial samples for non-ground truth classes at different levels of intensity, enabling tunable benchmarks for the evaluation of false positives. We achieve competitive performance in terms of net $L_2$ distortion compared to state-of-the-art benchmark techniques on CIFAR-10 and ImageNet; however, we demonstrate our framework achieves such results with simple distortions like Gaussian noise without introducing unnatural artifacts or color bleeds. This is made possible by a model-based reinforcement learning (RL) agent and a technique that reduces a deep tree search of the image for model sensitivity to perturbations, to a one-level analysis and action. The flexibility of choosing distortions and setting classification probability thresholds for multiple classes makes our framework suitable for algorithmic audits.
DOI: 10.5281/zenodo.8034832
title: Data from "Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness"

description: This repository contains the data from the paper, "Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness." Relevant URLs: https://hewlettpackard.github.io/trust-ml/ https://github.com/HewlettPackard/trust-ml/ Abstract: We present a novel framework for generating adversarial benchmarks to evaluate the robustness of image classification models. The RLAB framework allows users to customize the types of distortions to be optimally applied to images, which helps address the specific distortions relevant to their deployment. The benchmark can generate datasets at various distortion levels to assess the robustness of different image classifiers. Our results show that the adversarial samples generated by our framework with any of the image classification models, like ResNet-50, Inception-V3, and VGG-16, are effective and transferable to other models causing them to fail. These failures happen even when these models are adversarially retrained using state-of-the-art techniques, demonstrating the generalizability of our adversarial samples. Our framework also allows the creation of adversarial samples for non-ground truth classes at different levels of intensity, enabling tunable benchmarks for the evaluation of false positives. We achieve competitive performance in terms of net $L_2$ distortion compared to state-of-the-art benchmark techniques on CIFAR-10 and ImageNet; however, we demonstrate our framework achieves such results with simple distortions like Gaussian noise without introducing unnatural artifacts or color bleeds. This is made possible by a model-based reinforcement learning (RL) agent and a technique that reduces a deep tree search of the image for model sensitivity to perturbations, to a one-level analysis and action. The flexibility of choosing distortions and setting classification probability thresholds for multiple classes makes our framework suitable for algorithmic audits.
DOI: 10.6084/m9.figshare.23271638
title: Replication files for "Broadcasting Messages via Telegram: Pro-government Social Media Control During the 2020 Protests in Belarus and 2022 Anti-war Protests in Russia"

description: The files include the replication data (dataset, code, and output) for "Broadcasting Messages via Telegram: Pro-government Social Media Control During the 2020 Protests in Belarus and 2022 Anti-war Protests in Russia"
DOI: 10.57967/hf/0757
title: AmericanStories
DOI: 10.5281/zenodo.8034880
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Vernon Ahmadjian, http://www.wikidata.org/entity/Q3289736. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q3289736
DOI: 10.5281/zenodo.8034879
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Vernon Ahmadjian, http://www.wikidata.org/entity/Q3289736. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q3289736
DOI: 10.5281/zenodo.8034882
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by João Manuel Antonio do Amaral Franco, http://www.wikidata.org/entity/Q4492402. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q4492402
DOI: 10.5281/zenodo.8034881
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by João Manuel Antonio do Amaral Franco, http://www.wikidata.org/entity/Q4492402. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q4492402
DOI: 10.5281/zenodo.8034886
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Carlos Ameghino, http://www.wikidata.org/entity/Q5041758. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5041758
DOI: 10.5281/zenodo.8034885
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Carlos Ameghino, http://www.wikidata.org/entity/Q5041758. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5041758
DOI: 10.5281/zenodo.8034890
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Kristian Andreassen, http://www.wikidata.org/entity/Q100935946. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q100935946
DOI: 10.5281/zenodo.8034889
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Kristian Andreassen, http://www.wikidata.org/entity/Q100935946. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q100935946
DOI: 10.5281/zenodo.8034894
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Antoni Andrzejowski, http://www.wikidata.org/entity/Q2090424. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q2090424
DOI: 10.5281/zenodo.8034893
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Antoni Andrzejowski, http://www.wikidata.org/entity/Q2090424. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q2090424
DOI: 10.5281/zenodo.8034896
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Martin T. Anfinnsen, http://www.wikidata.org/entity/Q105886106. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q105886106
DOI: 10.5281/zenodo.8034895
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Martin T. Anfinnsen, http://www.wikidata.org/entity/Q105886106. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q105886106
DOI: 10.3886/e192174
title: Is There an Idealized Target of Sexual Harassment in the MeToo Era?

description: The data and do-file accompany the following article, and can be used to replicate its findings.<br><br> Hart, Chloe Grace. 2023. “Is There an Idealized Target of Sexual Harassment in the MeToo Era?” Social Problems spad016. doi: 10.1093/socpro/spad016. <br><br>
DOI: 10.3886/e192174v1
title: Is There an Idealized Target of Sexual Harassment in the MeToo Era?

description: The data and do-file accompany the following article, and can be used to replicate its findings.<br><br> Hart, Chloe Grace. 2023. “Is There an Idealized Target of Sexual Harassment in the MeToo Era?” Social Problems spad016. doi: 10.1093/socpro/spad016. <br><br>
DOI: 10.5281/zenodo.8034902
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Enrique Pérez Arbeláez, http://www.wikidata.org/entity/Q21522815. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21522815
DOI: 10.5281/zenodo.8034901
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Enrique Pérez Arbeláez, http://www.wikidata.org/entity/Q21522815. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21522815
DOI: 10.5281/zenodo.8034906
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Eleonora Armitage, http://www.wikidata.org/entity/Q21505331. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21505331
DOI: 10.5281/zenodo.8034905
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Eleonora Armitage, http://www.wikidata.org/entity/Q21505331. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21505331
DOI: 10.5281/zenodo.8034914
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Blanca Renée Arrillaga, http://www.wikidata.org/entity/Q5729816. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5729816
DOI: 10.5281/zenodo.8034913
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Blanca Renée Arrillaga, http://www.wikidata.org/entity/Q5729816. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5729816
DOI: 10.5281/zenodo.8034918
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Louisa Atkinson, http://www.wikidata.org/entity/Q6688489. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q6688489
DOI: 10.5281/zenodo.8034917
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Louisa Atkinson, http://www.wikidata.org/entity/Q6688489. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q6688489
DOI: 10.5281/zenodo.8034922
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Alice Fay, http://www.wikidata.org/entity/Q109742037. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q109742037
DOI: 10.5281/zenodo.8034921
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Alice Fay, http://www.wikidata.org/entity/Q109742037. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q109742037
DOI: 10.5281/zenodo.8034924
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Clara Baadsnes, http://www.wikidata.org/entity/Q107643047. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107643047
DOI: 10.5281/zenodo.8034923
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Clara Baadsnes, http://www.wikidata.org/entity/Q107643047. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q107643047