cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.2591698
title: On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits

description: MESA inlists associated with On the Observability of Individual Population III Stars and Their Stellar-mass Black Hole Accretion Disks through Cluster Caustic Transits
DOI: 10.6073/pasta/a5f7a769fd1f3f75213b814a3c377f2e
title: SGS-LTER Long-term Monitoring Project: Spotlight Rabbit Count on the Central Plains Experimental Range, Nunn, Colorado, USA 1994-2006, ARS Study Number 98 (Reformatted to ecocomDP Design Pattern)

description: This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org.

This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=136&revision=17

The abstract below was extracted from the Level 0 data package and is included for context:
DOI: 10.5281/zenodo.2591708
title: He-accreting carbon-oxygen white dwarfs and Type Ia supernovae

description: MESA inlists associated with He-accreting carbon-oxygen white dwarfs and Type Ia supernovae
DOI: 10.5281/zenodo.2591709
title: He-accreting carbon-oxygen white dwarfs and Type Ia supernovae

description: MESA inlists associated with He-accreting carbon-oxygen white dwarfs and Type Ia supernovae
DOI: 10.5281/zenodo.2591710
title: Analyzing the importance of spatial autocorrelation in hyperparameter tuning and performance estimation of machine-learning algorithms for spatial data.

description: This repository will contain the research compendium of our work on comparing algorithms across different resampling settings.
DOI: 10.6073/pasta/ed3fe1314a362f519b3339b9de357c68
title: Pika demography data for west knoll and Indian Peaks wilderness, 2008 - ongoing

description: Pikas are captured, anesthetized, marked with colored ear-tags, non-lethally sampled, and released at point of capture during June-October. Study sites include a gradient of elevation and slope aspect, allowing a comparative study of pika response to variation in climate and sub-surface microclimate. Daily variation in snow cover and sub-surface temperatures are measured using data loggers placed within the territories of marked pikas. Focal territories are revisited at least once to characterize available vegetation via transect sampling and at least annually to service data loggers and record pika survival. Samples collected for genetic and physiological studies include ectoparasites, blood, saliva, urine, feces and hair as well as records of sex, stage, reproductive status, weight, foot length and body temperature.
DOI: 10.5281/zenodo.2591280
title: Image Synthesis with a Convolutional Capsule Generative Adversarial Network- Prepared Data

description: A set of prepared datasets for running experiments to replicate paper (see below).

List of data:

Training capspix2pix:


	crops256.zip - folder containing 256x256 crops from the original dataset for training capspix2pix. Images are in the "train/original" folder, and labels are in the "train/mask" folder.
	syn256_x_data_val.npy + syn256_y_data_val.npy + syn256_y_points_data_val.npy (images + labels + centrelines) - validation synthetic dataset, used while training capspix2pix for plotting


Training u-net:


	capspix2pix_AR_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from real labels
	capspix2pix_SSM_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from synthetic labels
	PBAM_SSM_data_train.npy + PBAM_SSM_mask_train.npy (images + labels) - data generated from PBAM (Physics-based model) for training u-net
	pix2pix_AR_data_train.npy + pix2pix_AR_mask_train.npy (images + labels) - data generated from a pix2pix model from real labels for training u-net
	pix2pix_SSM_data_train.npy + pix2pix_SSM_mask_train.npy (images + labels) - data generated from a pix2pix model from synthetic labels for training u-net
	real_data_data_train.npy + real_data_mask_train.npy (images + labels) - augmented real dataset for training u-net


Testing u-net:


	org64_data_test.npy + org64_mask_test.npy (images + labels) - crops from original test dataset for testing u-net


Interpolation:


	crops256_inter_data_train.npy + crops256_inter_mask_train.npy (images + labels) - example data for interpolation


<strong>Please cite the following paper when using this dataset:</strong>

Bass, C., Dai, T., Billot, B.,  Arulkumaran, K., Creswell, A., Clopath, C., De Paola, V., and Bharath, A. A., 2019. “Image synthesis with a convolutional capsule generative adversarial network,” <em>Medial Imaging with Deep Learning.</em>

<strong>See Github page for further instructions:</strong>

https://github.com/CherBass/CapsPix2Pix
DOI: 10.5281/zenodo.2591281
title: Image Synthesis with a Convolutional Capsule Generative Adversarial Network- Prepared Data

description: A set of prepared datasets for running experiments to replicate paper (see below).

List of data:

Training capspix2pix:


	crops256.zip - folder containing 256x256 crops from the original dataset for training capspix2pix. Images are in the "train/original" folder, and labels are in the "train/mask" folder.
	syn256_x_data_val.npy + syn256_y_data_val.npy + syn256_y_points_data_val.npy (images + labels + centrelines) - validation synthetic dataset, used while training capspix2pix for plotting


Training u-net:


	capspix2pix_AR_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from real labels
	capspix2pix_SSM_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from synthetic labels
	PBAM_SSM_data_train.npy + PBAM_SSM_mask_train.npy (images + labels) - data generated from PBAM (Physics-based model) for training u-net
	pix2pix_AR_data_train.npy + pix2pix_AR_mask_train.npy (images + labels) - data generated from a pix2pix model from real labels for training u-net
	pix2pix_SSM_data_train.npy + pix2pix_SSM_mask_train.npy (images + labels) - data generated from a pix2pix model from synthetic labels for training u-net
	real_data_data_train.npy + real_data_mask_train.npy (images + labels) - augmented real dataset for training u-net


Testing u-net:


	org64_data_test.npy + org64_mask_test.npy (images + labels) - crops from original test dataset for testing u-net


Interpolation:


	crops256_inter_data_train.npy + crops256_inter_mask_train.npy (images + labels) - example data for interpolation


<strong>Please cite the following paper when using this dataset:</strong>

Bass, C., Dai, T., Billot, B.,  Arulkumaran, K., Creswell, A., Clopath, C., De Paola, V., and Bharath, A. A., 2019. “Image synthesis with a convolutional capsule generative adversarial network,” <em>Medial Imaging with Deep Learning.</em>

<strong>See Github page for further instructions:</strong>

https://github.com/CherBass/CapsPix2Pix
DOI: 10.5063/f1t151xn
title: Commercial salmon harvest data: gross earnings and number of fish, Alaska, 1975-2016

description: This dataset contains annual commercial salmon harvest information from fisheries in Alaska from 1975-2016, provided by the Alaska Department of Fish and Game (ADF&amp;G). Included are the number of fish caught by salmon species, the number of people and permits issued, and the number of fish processors used, and vessels used. Three files are included with differing geographic resolutions, which from coarse to fine consist of spatial resolutions: commercial fishing area, commercial fishing district, and commercial fishing subdistrict. All files are annual with the exception of one, which organizes harvest data by statistical week. This time scale facilitates aggregated catch comparisons between years. Note that some rows within each file are marked as confidential when the number of either permits, people, or processors is under 3. Finer spatial or temporal resolution datasets result in more confidential rows. These data are provided to facilitate understanding of commercial harvest of salmon in Alaska, and how this harvest changes both over time and space. Data shown here were modified slightly from what was provided by (ADF&amp;G) by replacing internal species and gear codes with more readily understandable species names and gear descriptions.
DOI: 10.25912/5c883949ee806
title: REACH Project: Healthcare associated infections dataset 2019
DOI: 10.17632/hwpnvmrgff.1
title: Data for: Timber-framed building damage from tephra fall and lahar: 2015 Calbuco eruption, Chile

description: Data for: Timber-framed building damage from tephra fall and lahar: 2015 Calbuco eruption, Chile
DOI: 10.17632/wdxcfhjk97.1
title: Data for: Local Manufacturing for Sustainable Development: Decision Support for Small Enterprises

description: The Xpress Code is for use in Xpress. The data input file is for the case study described in the paper. The data output file is the output of the Xpress Code run with the data input file.
DOI: 10.5281/zenodo.2591744
title: Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection

description: MESA inlists associated with Aerts et al. (2018). MESA version 10108.

Publication DOI: 10.3847/1538-4365/aaccfb
DOI: 10.5281/zenodo.2591743
title: Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection

description: MESA inlists associated with Aerts et al. (2018). MESA version 10108.

Publication DOI: 10.3847/1538-4365/aaccfb
DOI: 10.17632/pkxx6k6pr4.1
title: Data for: Combining Machine Learning Algorithms and Geometric Morphometrics: A Study of Carnivore Tooth Marks

description: Morfologika files and landmark data for tooth marks studied in our analysis. These files can be opened in any software supporting this type of data including MorphoJ, Morfologika and R using the 'geomorph' package
DOI: 10.5281/zenodo.2591746
title: Analyzing the importance of spatial autocorrelation in hyperparameter tuning and performance estimation of machine-learning algorithms for spatial data.

description: This repository will contain the research compendium of our work on comparing algorithms across different resampling settings.
DOI: 10.14469/hpc/5106
title: RRS Def2TZVPP 31.49 --1690.529696 +BJ

description: Gaussian Calculation
DOI: 10.5281/zenodo.2591751
title: Analysis of suprathermal nuclear processes in the solar core plasma

description: MESA inlists associated with Voronchev et al. 2017. Mesa version 4050.

Publication DOI: 10.1088/1361-6471/aa5f30
DOI: 10.5281/zenodo.2591752
title: Analysis of suprathermal nuclear processes in the solar core plasma

description: MESA inlists associated with Voronchev et al. 2017. Mesa version 4050.

Publication DOI: 10.1088/1361-6471/aa5f30
DOI: 10.6073/pasta/0b292453f643fe6999e58789cd1e7053
title: SGS-LTER Long-Term Montioring Project: Arthropod Pitfall Trapping on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1998-2006, ARS Study Number 118 (Reformatted to ecocomDP Design Pattern)

description: This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org.

This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sgs&identifier=134&revision=17

The abstract below was extracted from the Level 0 data package and is included for context:
DOI: 10.5281/zenodo.2591754
title: The Evolution of Gas Giant Entropy During Formation by Runaway Accretion

description: MESA inlists associated with Berardo et al. (2017). MESA version 7624.

Publication DOI: 10.3847/1538-4357/834/2/149
DOI: 10.5517/ccdc.csd.cc202vhg
title: CCDC 1849785: Experimental Crystal Structure Determination

description: Related Article: Shan Jiang, Jiayu Wang, Qingkai Qi, Jingyu Qian, Bin Xu, Fangfei Li, Qiang Zhou, Wenjing Tian|2019|Chem.Commun.|55|3749|doi:10.1039/C9CC00234K
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.cc202vjh
title: CCDC 1849786: Experimental Crystal Structure Determination

description: Related Article: Shan Jiang, Jiayu Wang, Qingkai Qi, Jingyu Qian, Bin Xu, Fangfei Li, Qiang Zhou, Wenjing Tian|2019|Chem.Commun.|55|3749|doi:10.1039/C9CC00234K
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.cc218xx5
title: CCDC 1885417: Experimental Crystal Structure Determination

description: Related Article: Mark R. D. Gatus, Indrek Pernik, Joshua A. Tompsett, Samantha C. Binding, Matthew B. Peterson, Barbara A. Messerle|2019|Dalton Trans.|48|4333|doi:10.1039/C9DT00313D
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.cc21fwt6
title: CCDC 1890188: Experimental Crystal Structure Determination

description: Related Article: Jiangfeng Lu, Ning Zhang, Xiaowei Zhu, Qiaozhen Sun, Bingguang Zhang, Hao Liu, Bo Zhao|2019|Inorg.Chem.Commun.|103|53|doi:10.1016/j.inoche.2019.03.011
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.cc21fww8
title: CCDC 1890190: Experimental Crystal Structure Determination

description: Related Article: Jiangfeng Lu, Ning Zhang, Xiaowei Zhu, Qiaozhen Sun, Bingguang Zhang, Hao Liu, Bo Zhao|2019|Inorg.Chem.Commun.|103|53|doi:10.1016/j.inoche.2019.03.011
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.cc21p9bd
title: CCDC 1897303: Experimental Crystal Structure Determination

description: Related Article: Elizabeth A. Stone, Brandon Q. Mercado, Scott J. Miller|2019|Org.Lett.|21|2346|doi:10.1021/acs.orglett.9b00624
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.cc21pyvk
title: CCDC 1897939: Experimental Crystal Structure Determination

description: Related Article: Muhammad Kazim, Maxime A. Siegler, Thomas Lectka|2019|Org.Lett.|21|2326|doi:10.1021/acs.orglett.9b00615
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.cc21pywl
title: CCDC 1897940: Experimental Crystal Structure Determination

description: Related Article: Muhammad Kazim, Maxime A. Siegler, Thomas Lectka|2019|Org.Lett.|21|2326|doi:10.1021/acs.orglett.9b00615
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.cc21pyxm
title: CCDC 1897941: Experimental Crystal Structure Determination

description: Related Article: Muhammad Kazim, Maxime A. Siegler, Thomas Lectka|2019|Org.Lett.|21|2326|doi:10.1021/acs.orglett.9b00615
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: 10.5281/zenodo.2591753
title: The Evolution of Gas Giant Entropy During Formation by Runaway Accretion

description: MESA inlists associated with Berardo et al. (2017). MESA version 7624.

Publication DOI: 10.3847/1538-4357/834/2/149
DOI: 10.5517/ccdc.csd.cc202czg
title: CCDC 1849335: Experimental Crystal Structure Determination

description: Related Article: Wei-Ming Liao, Mei-Juan Wei, Jun-Ting Mo, Peng-Yan Fu, Ya-Nan Fan, Mei Pan, Cheng-Yong Su|2019|Dalton Trans.|48|4489|doi:10.1039/C9DT00539K
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.cc218lrp
title: CCDC 1885102: Experimental Crystal Structure Determination

description: Related Article: Pratip K. Dutta, Jyoti Chauhan, Mahesh Kumar Ravva, Subhabrata Sen|2019|Org.Lett.|21|2025|doi:10.1021/acs.orglett.9b00150
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.cc218pvw
title: CCDC 1885198: Experimental Crystal Structure Determination

description: Related Article: Pratip K. Dutta, Jyoti Chauhan, Mahesh Kumar Ravva, Subhabrata Sen|2019|Org.Lett.|21|2025|doi:10.1021/acs.orglett.9b00150
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.cc21fws5
title: CCDC 1890187: Experimental Crystal Structure Determination

description: Related Article: Jiangfeng Lu, Ning Zhang, Xiaowei Zhu, Qiaozhen Sun, Bingguang Zhang, Hao Liu, Bo Zhao|2019|Inorg.Chem.Commun.|103|53|doi:10.1016/j.inoche.2019.03.011
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.cc21gb84
title: CCDC 1890605: Experimental Crystal Structure Determination

description: Related Article: Ling Zhang, Peng Chen, Hong-Feng Li, Yong-Mei Tian, Peng-Fei Yan, Wen-Bin Sun|2019|Dalton Trans.|48|4324|doi:10.1039/C9DT00210C
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.cc21gb95
title: CCDC 1890606: Experimental Crystal Structure Determination

description: Related Article: Ling Zhang, Peng Chen, Hong-Feng Li, Yong-Mei Tian, Peng-Fei Yan, Wen-Bin Sun|2019|Dalton Trans.|48|4324|doi:10.1039/C9DT00210C
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.cc21gbb6
title: CCDC 1890607: Experimental Crystal Structure Determination

description: Related Article: Ling Zhang, Peng Chen, Hong-Feng Li, Yong-Mei Tian, Peng-Fei Yan, Wen-Bin Sun|2019|Dalton Trans.|48|4324|doi:10.1039/C9DT00210C
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.cc21gbc7
title: CCDC 1890608: Experimental Crystal Structure Determination

description: Related Article: Ling Zhang, Peng Chen, Hong-Feng Li, Yong-Mei Tian, Peng-Fei Yan, Wen-Bin Sun|2019|Dalton Trans.|48|4324|doi:10.1039/C9DT00210C
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.cc21vx4z
title: CCDC 1902691: Experimental Crystal Structure Determination

description: Related Article: Qi Xing,  Chun-Ming Chan,  Yiu-Wai Yeung,  Wing-Yiu Yu|2019|J.Am.Chem.Soc.|141|3849|doi:10.1021/jacs.9b00535
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.