cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7055264
title: IODP Expedition 352 X-ray diffraction (XRD)

description: X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).
DOI: 10.6084/m9.figshare.20993944
title: Supplemental tables

description: <strong>Table S1. Patient Demographics</strong> <strong>Table S2. PCR primer sequences</strong> <strong>Table S3. Immunohistochemistry and Flow Cytometry Antibodies</strong>
DOI: 10.6084/m9.figshare.20993944.v2
title: Supplemental tables

description: <strong>Table S1. Patient Demographics</strong> <strong>Table S2. PCR primer sequences</strong> <strong>Table S3. Immunohistochemistry and Flow Cytometry Antibodies</strong>
DOI: 10.6084/m9.figshare.20993944.v1
title: Supplemental tables

description: <strong>Table S1. Patient Demographics</strong> <strong>Table S2. PCR primer sequences</strong> <strong>Table S3. Immunohistochemistry and Flow Cytometry Antibodies</strong>
DOI: 10.5281/zenodo.6114162
title: Six new species of Pristimantis (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park

description: Aligned DNA sequence matrix for phylogenetic analyses of the article "Six new species of <em>Pristimantis</em> (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park in Amazonian cloud forests of Ecuador". The matrix is in NEXUS format and contains the DNA matrix of sequences of 4 concatenated genes. Genes are arranged as follows: charset 16S = 1 -1386;<br> charset RAG1 codon position 1 = 1387 -1966 \ 3;<br> charset RAG1 codon position 2 = 1388 -1967 \ 3;<br> charset RAG1 codon position 3 = 1389 -1968 \ 3;<br> charset 12S = 1969 -2992;<br> charset nonCoding = 2993 - 3068 4026 - 4155;<br> charset ND1 codon position 1 = 3069 -4023 \ 3;<br> charset ND1 codon position 2 = 3070 -4024 \ 3;<br> charset ND1 codon position 3 = 3071 -4025 \ 3;
DOI: 10.5281/zenodo.6114163
title: Six new species of Pristimantis (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park

description: Aligned DNA sequence matrix for phylogenetic analyses of the article "Six new species of <em>Pristimantis</em> (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park in Amazonian cloud forests of Ecuador". The matrix is in NEXUS format and contains the DNA matrix of sequences of 4 concatenated genes. Genes are arranged as follows: charset 16S = 1 -1386;<br> charset RAG1 codon position 1 = 1387 -1966 \ 3;<br> charset RAG1 codon position 2 = 1388 -1967 \ 3;<br> charset RAG1 codon position 3 = 1389 -1968 \ 3;<br> charset 12S = 1969 -2992;<br> charset nonCoding = 2993 - 3068 4026 - 4155;<br> charset ND1 codon position 1 = 3069 -4023 \ 3;<br> charset ND1 codon position 2 = 3070 -4024 \ 3;<br> charset ND1 codon position 3 = 3071 -4025 \ 3;
DOI: 10.5281/zenodo.7055252
title: Six new species of Pristimantis (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park

description: Aligned DNA sequence matrix for phylogenetic analyses of the article "Six new species of <em>Pristimantis</em> (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park in Amazonian cloud forests of Ecuador". The matrix is in NEXUS format and contains the DNA matrix of sequences of 4 concatenated genes. Genes are arranged as follows: charset 16S = 1 -1386;<br> charset RAG1 codon position 1 = 1387 -1966 \ 3;<br> charset RAG1 codon position 2 = 1388 -1967 \ 3;<br> charset RAG1 codon position 3 = 1389 -1968 \ 3;<br> charset 12S = 1969 -2992;<br> charset nonCoding = 2993 - 3068 4026 - 4155;<br> charset ND1 codon position 1 = 3069 -4023 \ 3;<br> charset ND1 codon position 2 = 3070 -4024 \ 3;<br> charset ND1 codon position 3 = 3071 -4025 \ 3;
DOI: 10.5281/zenodo.7055289
title: Six new species of Pristimantis (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park

description: Aligned DNA sequence matrix for phylogenetic analyses of the article "Six new species of <em>Pristimantis</em> (Anura: Strabomantidae) from Llanganates National Park and Sangay National Park in Amazonian cloud forests of Ecuador". The matrix is in NEXUS format and contains the DNA matrix of sequences of 4 concatenated genes. Genes are arranged as follows: charset 16S = 1 -1386;<br> charset RAG1 codon position 1 = 1387 -1966 \ 3;<br> charset RAG1 codon position 2 = 1388 -1967 \ 3;<br> charset RAG1 codon position 3 = 1389 -1968 \ 3;<br> charset 12S = 1969 -2992;<br> charset nonCoding = 2993 - 3068 4026 - 4155;<br> charset ND1 codon position 1 = 3069 -4023 \ 3;<br> charset ND1 codon position 2 = 3070 -4024 \ 3;<br> charset ND1 codon position 3 = 3071 -4025 \ 3;
DOI: 10.5281/zenodo.7055271
title: IODP Expedition 352 Whole-round core section composite 360 degree images

description: Images of the outside of hard rock whole-round sections were acquired using a linescan imager (Section Half Imaging Logger [SHIL]) and a special holder that allows each 90 degree segment of the outer surface to be positioned properly. The images were taken at a resolution of 20 lines/mm (50 micropixels). JRSO staff take these quadrant images and compile them into a side-by-side rollout photograph of the section. Composite images are available as both JPG and TIF image formats. Individual quadrant images are available as JPG images only through this report; contact the IODP-JRSO Data Librarian if quadrant TIF files (~160 MB) are needed.
DOI: 10.5281/zenodo.7055270
title: IODP Expedition 352 Whole-round core section composite 360 degree images

description: Images of the outside of hard rock whole-round sections were acquired using a linescan imager (Section Half Imaging Logger [SHIL]) and a special holder that allows each 90 degree segment of the outer surface to be positioned properly. The images were taken at a resolution of 20 lines/mm (50 micropixels). JRSO staff take these quadrant images and compile them into a side-by-side rollout photograph of the section. Composite images are available as both JPG and TIF image formats. Individual quadrant images are available as JPG images only through this report; contact the IODP-JRSO Data Librarian if quadrant TIF files (~160 MB) are needed.
DOI: 10.5281/zenodo.5915598
title: Inference and Test Generation Using Program Invariants in Chemical Reaction Networks Artifacts

description: The artifacts for Inference and Test Generation Using Program Invariants in Chemical Reaction Networks, published at ICSE 2022. The pdf of the paper can be accessed at IEEEXplore To cite this work, please use the citation below <pre>@INPROCEEDINGS{9794130, author={Gerten, Michael C. and Marsh, Alexis L. and Lathrop, James I. and Cohen, Myra B. and Miner, Andrew S. and Klinge, Titus H.}, booktitle={2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)}, title={Inference and Test Generation Using Program Invariants in Chemical Reaction Networks}, year={2022}, volume={}, number={}, pages={1193-1205}, doi={10.1145/3510003.3510176}}</pre> The artifacts are also available at<strong> https://github.com/LavaOps/ICSE-2022-Artifacts</strong>
description: This material is based upon work supported by the National Science Foundation under Grant CCF #1909688 and FET #1900716.
DOI: 10.5281/zenodo.6620698
title: Inference and Test Generation Using Program Invariants in Chemical Reaction Networks Artifacts

description: The artifacts for Inference and Test Generation Using Program Invariants in Chemical Reaction Networks, published at ICSE 2022. The pdf of the paper can be accessed at IEEEXplore. To cite this work, please use the citation below: <pre>@INPROCEEDINGS{GertenICSE22, author={Gerten, Michael C. and Marsh, Alexis L. and Lathrop, James I. and Cohen, Myra B. and Miner, Andrew S. and Klinge, Titus H.}, booktitle={2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)}, title={Inference and Test Generation Using Program Invariants in Chemical Reaction Networks}, month={May}, year={2022}, pages={1193-1205}, doi={10.1145/3510003.3510176}}</pre> The artifacts are also available on Github. <strong>This is an updated version of the ChemFlow tool. The update addressed an overflow error when computing gaussian elimination that could result in incorrect invariants with certain model inputs. After verification, all models in this work were not affected by this bug and have the same set of invariants generated by both versions. We have updated the docker file to use the new code as well.</strong>
description: We would like to thank C. Henry, J.P. Faria and B. Cottingham for feedback and discussions on the E. coli invariants. This material is based upon work supported by the National Science Foundation under Grant CCF #1909688 and FET #1900716. Disclaimer: "Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation."
DOI: 10.5517/ccdc.csd.cc13z9yb
title: CCDC 1042032: Experimental Crystal Structure Determination

description: Related Article: Guang-Yao Bai, Zhi-Yong Wu, Jin-Lei Xing, Yan-Tuan Li|2023|J.Mol.Struct.|1271|134035|doi:10.1016/j.molstruc.2022.134035
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bzf81
title: CCDC 2174193: Experimental Crystal Structure Determination

description: Related Article: Ş. Çakmak, T. Aycan, F. Öztürk, A. Veyisoğlu|2022|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|78|493|doi:10.1107/S2053229622008257
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20995345
title: Retrospective confidence as metacognitive measure

description: Metacognition – the ability of individuals to monitor one’s own cognitive performance and decisions – is often studied empirically based on the retrospective confidence ratings. In experimental research, participants are asked to report how sure they are in their response, or to report how well their performance in high-level cognitive or low-level perceptual tasks is. These retrospective confidence ratings are used as a measure of monitoring effectiveness: larger difference in confidence ratings assigned to correct and incorrect responses reflects better ability to estimate the likelihood of making an error by an experiment participant, or better metacognitive monitoring ability. We discuss this underlying assumption and provide some methodological consideration that might interfere with interpretation of results, depending on what is being asked to evaluate, how the confidence response is elicited, and the overall proportion of different trial types within one experimental session. We conclude that mixing trials on which decision confidence is assigned when positive evidence needs to be evaluated and the trials on which absence of positive evidence needs to be evaluated should be avoided. These considerations might be important when designing experimental work to explore metacognitive efficiency using retrospective confidence ratings.
DOI: 10.6084/m9.figshare.20995384
title: MERFISH probe target region sequences

description: Sequences for target regions of MERFISH probes used in gene panel
DOI: 10.5281/zenodo.7055340
title: IODP Expedition 352 Moisture and Density

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.
DOI: 10.5281/zenodo.7055339
title: IODP Expedition 352 Moisture and Density

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.
DOI: 10.34681/wjbs-n581
title: State Child Abuse and Neglect (SCAN) Policies Database 2019-2021

description: The State Child Abuse and Neglect (SCAN) Policies Database, supported by the Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human services, compiles data on state definitions and policies related to the surveillance of child maltreatment incidence and associated risk and protective factors.

The SCAN Policies Database is a resource for researchers, analysts, and others who are interested in examining differences in definitions and policies on child maltreatment across states and overtime. A primary use of these data is to allow researchers to link the analytic files to other data sources to address important questions about how variations in states’ definitions and policies are associated with the incidence of child maltreatment, the child welfare system response, and ultimately child safety and well-being.

Other data sources that can be linked with the SCAN Policies Database include data from the National Child Abuse and Neglect Data System (NCANDS), the Adoption and Foster Care Analysis and Reporting System (AFCARS), state administrative data, and survey data. When data from the SCAN Policies Database are linked with other data sources, these data can be used to answer key research questions about how variations in definitions and policies are associated with key aspects of understanding the incidence of child abuse and neglect.

The SCAN Policies Database includes state definitions and policies from the 50 states, the District of Columbia, and the Commonwealth of Puerto Rico. The SCAN Policies Database 2019 represents data, collected, reviewed, and verified between May 2019 and July 2020, and the data reflect the state definitions and policies for the calendar year 2019. The SCAN Policies Database 2021 represents data collected, reviewed, and verified between July 2021 and January 2022, and the data reflect the state definitions and policies for the calendar year 2021.
DOI: 10.34681/14t8-8730
title: State Child Abuse and Neglect (SCAN) Policies Database 2019

description: The State Child Abuse and Neglect (SCAN) Policies Database, supported by the Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human services, compiles data on state definitions and policies related to the surveillance of child maltreatment incidence and associated risk and protective factors. The SCAN Policies Database is a resource for researchers, analysts, and others who are interested in examining differences in definitions and policies on child maltreatment across states. A primary use of these data is to allow researchers to link the analytic files to other data sources to address important questions about how variations in states’ definitions and policies are associated with the incidence of child maltreatment, the child welfare system response, and ultimately child safety and well-being. Other data sources that can be linked with the SCAN Policies Database include data from the National Child Abuse and Neglect Data System (NCANDS), the Adoption and Foster Care Analysis and Reporting System (AFCARS), state administrative data, and survey data. When data from the SCAN Policies Database are linked with other data sources, these data can be used to answer key research questions about how variations in definitions and policies are associated with key aspects of understanding the incidence of child abuse and neglect. The SCAN Policies Database includes state definitions and policies from the 50 states, the District of Columbia, and the Commonwealth of Puerto Rico. The data were collected from a review of statutes and state documentation between May 2019 - June 2020.
To learn more about the SCAN Policies Database project, explore the data online, or download a comma separated file (.csv), please visit https://scanpoliciesdatabase.com.
*Note: The NDACAN version of the SCAN Policies Database is identical to the data available for download from the SCAN Policies Database webpage but is offered in a wider variety of file formats including: SAS, SPSS, Stata, and a tab-delimited data file for use with spreadsheet programs and R. All file formats for statistical software programs contain variable and value labels.
DOI: 10.5281/zenodo.7055305
title: IODP Expedition 352 Scanning electron microscope images

description: Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.
DOI: 10.5281/zenodo.7055304
title: IODP Expedition 352 Scanning electron microscope images

description: Microscopic images of discrete samples were acquired using a scanning electron microscope (SEM) and captured as image files. These files were uploaded along with a brief description and a record of the microscopic conditions when the image was taken.
DOI: 10.5281/zenodo.7055446
title: IODP Expedition 352 Magnetic susceptibility (whole round)

description: Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
DOI: 10.5281/zenodo.7055445
title: IODP Expedition 352 Magnetic susceptibility (whole round)

description: Magnetic susceptibility was measured on whole-round sections (and rarely section halves) on the Whole-Round Multisensor Logger (WRMSL) and/or Special Task Multisensor Logger (STMSL) using a Bartington MS2 meter and a 90 mm or 80 mm MS2C loop. As volume of the sample is not controlled for this experiment, susceptibility units are recorded in instrument units and are not volume-corrected.
DOI: 10.5281/zenodo.7055451
title: IODP Expedition 352 Magnetic susceptibility (point or contact system)

description: Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).
DOI: 10.5281/zenodo.7055450
title: IODP Expedition 352 Magnetic susceptibility (point or contact system)

description: Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).
DOI: 10.6084/m9.figshare.20485914.v1
title: TRAF6_screen

description: This repository contains data and analysis associated with a manuscript entitled: <strong>Molecular determinants of TRAF6 binding specificity suggest that native interaction partners are not optimized for affinity </strong>(DOI: 10.1002/pro.4429)
DOI: 10.34740/kaggle/ds/2435762
title: Mexico Hourly Air Pollution (2010-2021)
DOI: 10.1184/r1/20732656
title: Unpreprocessed Dataset for Idiomatic ReTyping (DIRT)

description: This is the full, unpreprocessed DIRT dataset referenced by our paper "Augmenting Decompiler Output with Learned Variable Names and Types". For more information see README.txt.
DOI: 10.1184/r1/20732656.v1
title: Unpreprocessed Dataset for Idiomatic ReTyping (DIRT)

description: This is the full, unpreprocessed DIRT dataset referenced by our paper "Augmenting Decompiler Output with Learned Variable Names and Types". For more information see README.txt.
DOI: 10.6084/m9.figshare.20485914
title: TRAF6_screen

description: This repository contains data and analysis associated with a manuscript entitled: <strong>Molecular determinants of TRAF6 binding specificity suggest that native interaction partners are not optimized for affinity </strong>(DOI: 10.1002/pro.4429)
DOI: 10.6084/m9.figshare.20485914.v3
title: TRAF6_screen

description: This repository contains data and analysis associated with a manuscript entitled: <strong>Molecular determinants of TRAF6 binding specificity suggest that native interaction partners are not optimized for affinity </strong>(DOI: 10.1002/pro.4429)
DOI: 10.6084/m9.figshare.20485914.v2
title: TRAF6_screen

description: This repository contains data and analysis associated with a manuscript entitled: <strong>Molecular determinants of TRAF6 binding specificity suggest that native interaction partners are not optimized for affinity </strong>(DOI: 10.1002/pro.4429)
DOI: 10.6084/m9.figshare.3761562.v2333
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.7055475
title: IODP Expedition 352 Portable X-ray fluorescence (p-XRF)

description: Energy-Dispersive X-Ray Fluorescence (ED-XRF) is a rapid, non-destructive technique for determining qualitative and quantitative changes in chemical composition. Aboard the JOIDES Resolution, pXRF is used for measuring points on section halves, rock pieces, and sometimes powders. Spots are typically irradiated at multiple conditions to excite and measure a wide range of elements. The peak intensity changes (we do not provide concentrations) are then used to help recognize and define major chemo-stratigraphic units without the need for destructive sampling.