cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.884963
title: Growth increment width measurement and SGIshell data, Kassel Formation, Kassel Basin, middle Chattian (2009-KS6-D17L)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.884966
title: Growth increment width measurement and SGIshell data, Kassel Formation, Kassel Basin, middle Chattian (2009-KS6-D33R)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.884962
title: Growth increment width measurement and SGIshell data, Kassel Formation, Kassel Basin, middle Chattian (2009-KS6-D16L)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.918236
title: Belowground soil analysis from the Tibetan Plateau
DOI: 10.1594/pangaea.884965
title: Growth increment width measurement and SGIshell data, Kassel Formation, Kassel Basin, middle Chattian (2009-KS6-D23R)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.895644
title: Data set on carbon and nitrogen concentrations, stocks, and isotopic composition in Red Sea seagrass and mangrove sediments

description: Data on carbon and nitrogen stocks and stable isotope composition (δ13C, δ15N) in Red Sea seagrass and mangrove sediments
description: The dataset is publically available since May 2019.
description: Supplement to: Garcias-Bonet, Neus; Delgado Huertas, Antonio; Carrillo-de-Albornoz, Paloma; Anton, Andrea; Almahasheer, Hanan; Marbà, Núria; Hendriks, Iris; Krause-Jensen, Dorte; Duarte, Carlos Manuel (2019): Carbon and nitrogen concentrations, stocks, and isotopic compositions in Red Sea seagrass and mangrove sediments. Frontiers in Marine Science, 6, 267
DOI: 10.1594/pangaea.884927
title: Growth increment width measurement and SGIshell data, Alzey Formation, Mainz Basin, middle Rupelian (EOW-Arc-Zeil-F1X)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.882176
title: National Forest Inventory of Mexico 2009-2012

description: This dataset was updated on 2018-02-15, biomasses and C content were addded.
DOI: 10.1594/pangaea.884924
title: Growth increment width measurement and SGIshell data, Alzey Formation, Mainz Basin, middle Rupelian (MB-Wht-9)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.933143
title: Planktic foraminifera and stable isotope record of sediment core OCE2017-GR02-GC

description: The dataset consists of the total abundance of planktic foraminifera, the relative abundances of planktic foraminiferal species, and planktic and benthic oxygen and carbon stable isotope ratios of the uppermost 18.5 cm of gravity core OCE2017-GR02-GC. The core was retrieved from a plateau on the northeastern Greenland continental slope (77º05'11 N, 5º19'53 W, 1200 m water depth) during an expedition of R/V Oceania in August 2017. Here we present the record from the uppermost 18.5 cm of the total 135 cm of core length. The core was sampled at 0.5 cm intervals in the uppermost 10.5 cm and at 2 cm intervals in the remaining part. Samples were freeze-dried, weighed, wet-sieved through a 63 μm sieve, and subsequently split into size fractions using 100 and 500 μm sieves. Counts of planktic foraminiferal assemblages were conducted on representative splits (&gt;300 specimens) of the 100–500 μm size fraction. Individual species were identified and counted. The number of planktic foraminifera per 1 g dry sediment as well as the percentage of individual species was calculated. Stable oxygen and carbon isotope analyses were conducted on planktic species Neogloboquadrina pachyderma and benthic species Cassidulina neoteretis. Approximately 25 pristine specimens of planktics and 10 specimens of benthics were picked from the 100–500 μm size fraction. All stable isotope analyses were performed at the Light Stable Isotope Mass Spec Laboratory, Department of Geological Sciences, University of Florida, USA using a Kiel III carbonate preparation device coupled with a Finnigan-Mat 252 isotope ratio mass spectrometer. Each batch of samples was measured with 8 NBS-19 and 2 NBS-18 standards. Standard masses were 30-50 µg. Samples and standards were loaded in individual glass Kiel vials (round bottom with socket tops) and placed in a carousel which was inserted in the Kiel oven. Phosphoric acid with a specific gravity of 1.92 (at 25°C) was used. The reaction temperature was 70°C and the reaction time was 10 minutes. Results are expressed in the δ notation referring to the PDB standard and are given as δ18O and δ13C with an analytical accuracy of 0.04 and 0.02 ‰, respectively. The stable isotope data were not corrected for vital effect nor global ice volume. The data were acquired in 2020.
DOI: 10.1594/pangaea.973255
title: Turnover times of soil carbon and soil mean carbon ages based upon compound-specific radiocarbon data in sediment core GeoB7702-3

description: This dataset contains catchment-weighted turnover times of soil carbon (τsoil) and soil mean carbon ages (0-100m soil depth) for the Nile River watershed over the past 18,000 years. This data is calculated from compound-specific radiocarbon analysis of leaf-wax biomarkers (high molecular weight n-alkanoic acids) in marine sediment core GeoB7702-3, eastern Mediterranean Sea. The radiocarbon data are given as the reservoir age offsets between the biomarkers and the atmosphere which represents the 14C-age of the biomarkers at the time of deposition in the marine sediments at the core site.
DOI: 10.1594/pangaea.973253
title: Compound-specific radiocarbon analysis of plant-wax biomarkers in sediment core GeoB7702-3

description: This dataset comprises compound-specific radiocarbon data of plant-wax biomarkers (high molecular weight nalkanes and high molecular weight n-alkanoic acids) from marine sediment core GeoB7702-3, recovered from the eastern Mediterranean Sea. The record covers the last 18,000 years. The data was analyzed by Accelerator Mass Spectrometry (AMS) using the MiniCarbonDatingSystem (MICADAS) at the Alfred Wegener Institut, Helmholtz Zentrum für Polar und Meeresforschung, Bremerhaven, Germany (AWI). The radiocarbon data presented in this dataset are corrected for procedure blanks and are reported in the fraction modern carbon (F14C) and ∆14C notations. The reservoir age offset between the biomarkers and the atmosphere is given to express the age of the biomarkers at the time of deposition in the marine sediments at the core site.
DOI: 10.1594/pangaea.973254
title: Contents of Amino-Bacteriohopanepolyols in sediment core GeoB7702-3

description: This dataset contains abundances of Amino-Bacteriohopanepolyols (Amino-BHPs; bacterial biomarkers) in marine sediment core GeoB7702-3, continental margin off Israel/eastern Mediterranean Sea. The record covers the last 18,000 years. The compounds were analyzed by Ultra High Pressure Liquid Chromatography – Ultra High Resolution quadrupole time-of-flight tandem Mass Spectrometry (UHPLC – UHR-qTOF-MS). The data are presented as peak area and concentrations. Given the lack of appropriate standards for BHP-quantification, the concentrations are given in arbitrary units (peak area/µg sediment).
DOI: 10.1594/pangaea.884915
title: Growth increment width measurement and SGIshell data, Bilzen Formation, southern North Sea Basin, middle Rupelian (RGM.794117_F1R)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.884916
title: Growth increment width measurement and SGIshell data, Bilzen Formation, southern North Sea Basin, middle Rupelian (RGM.794117_F3R)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.756227
title: Benthic foraminifera of sediment core MD99-2286
DOI: 10.1594/pangaea.921005
title: Analysis of sediment organic matter (OM) during the wet season in San Andres, Colombia
DOI: 10.1594/pangaea.884922
title: Growth increment width measurement and SGIshell data, Alzey Formation, Mainz Basin, middle Rupelian (MB-Wht-4)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.884967
title: Growth increment width measurement and SGIshell data, Kassel Formation, Kassel Basin, middle Chattian (2009-KS6-D34R)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.773808
title: Relative abundances of benthic foraminifers of sediment core Svanic90_9004
DOI: 10.1594/pangaea.892498
title: Sediment survey for total phosphorus, organic and water content, dry bulk density in Darss-Zingst lagoons, Zempin, Hiddensee and Kuehlungsborn in June 2017

description: This data set contains the calculated mean values for water content, loss on ignition and dry bulk density (n=3), as well as the total phosphorus concentrations of the first 1.4 centimeter (n=4). The total phosphorus stocks (g m^-2) were calculated for the first centimeter (0-1cm).
description: Supplement to: Berthold, Maximilian; Zimmer, Dana; Reiff, Volker; Schumann, Rhena (2018): Phosphorus contents re-visited after 40 years in muddy and sandy sediments of a temperate lagoon system. Frontiers in Marine Science, 5:305
DOI: 10.1594/pangaea.251263
title: Benthic foraminifera abundance of Hole 96-620

description: Relative abundance: D = dominant, A = abundant, C = common, F = few, R = rare, T = trace, P = present (numerical values are abundance in percent)
DOI: 10.1594/pangaea.884917
title: Growth increment width measurement and SGIshell data, Alzey Formation, Mainz Basin, middle Rupelian (MB-Wht-2)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.874382
title: Country-level mangrove soil carbon stocks and losses
DOI: 10.1594/pangaea.884921
title: Growth increment width measurement and SGIshell data, Alzey Formation, Mainz Basin, middle Rupelian (MB-Wht-3)

description: SGI=standardized growth indices.
DOI: 10.1594/pangaea.981229
title: Seawater carbonate chemistry and oyster physiological performance

description: This study investigated the physiological responses of juvenile Pacific oyster Crassostrea gigas exposed for 81 days to current and ocean acidification and warming conditions (+3 ◦C, − 0.3 pH units) under two tidal treatments (0 vs. 30 % emersion) and two food levels (ad libitum vs. limited). We measured growth, reproduction, food ingestion, respiration, and biochemical traits like energy reserves and membrane fatty acids. At the experiment's end, oysters were challenged with a viral disease to assess the physiological cost of acclimation and potential trade-offs.This dataset is included in the OA-ICC data compilation maintained in the framework of the IAEA Ocean Acidification International Coordination Centre (see https://oa-icc.ipsl.fr). Original data were downloaded from SEANOE (see Source) by the OA-ICC data curator. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2024) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2025-04-17.
DOI: 10.34740/kaggle/dsv/11842690
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.15447509
title: FIShBOT Archive 2025-05-17

description: This dataset is a static snapshot of the FIShBOT data product before new data are aggregated. This version of fishbot is archived for reproducibility and is not updated. The data are aggregated from the FIShBOT system, which collects and processes oceanographic from fishery dependent and independent sources.
DOI: 10.5281/zenodo.15447510
title: FIShBOT Archive 2025-05-17

description: This dataset is a static snapshot of the FIShBOT data product before new data are aggregated. This version of fishbot is archived for reproducibility and is not updated. The data are aggregated from the FIShBOT system, which collects and processes oceanographic from fishery dependent and independent sources.
DOI: 10.5281/zenodo.15447511
title: NGS for MFC and ddPCR in AML
DOI: 10.5281/zenodo.15447512
title: NGS for MFC and ddPCR in AML
DOI: 10.21227/jxg6-3161
title: "CADx"

description: "This dataset comprises 3D coronary computed tomography angiography (CTA) volumes curated for binary classification of coronary artery disease (CAD). It includes labeled cases categorized as \u2018healthy\u2019 and \u2018CAD\u2019 based on clinical diagnosis, providing volumetric image data reconstructed from multiple 2D CTA slices per patient. The dataset is designed to support the development and benchmarking of machine learning models for automated CAD detection. Each volume is stored in NIfTI format, facilitating compatibility with popular medical imaging frameworks. The collection aims to accelerate research in cardiovascular imaging and promote reproducibility in CAD classification tasks. Comprehensive metadata and standardized preprocessing protocols accompany the dataset to ensure ease of use and integration."
DOI: 10.15468/dl.pn6zcq
title: Occurrence Download

description: A dataset listing the 4944 species recorded in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Psychodidae"
 ]
}

 The dataset's 4944 records were derived from 636 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002782-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11842901
title: Egypt Gold Prices | Daily Updated
DOI: 10.6084/m9.figshare.29091899
title: FIG8.docx

description: <b>Figure 8.</b> Error distribution of different models in predicting FP.
DOI: 10.34740/kaggle/dsv/11842954
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.34740/kaggle/dsv/11843075
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.10526261
title: E2MDOFBuildingResponse

description: This material is based upon work supported by the U.S. National Science Foundation under Grants No. 1612843 and No. 2131111. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.
DOI: 10.5281/zenodo.10526262
title: E2MDOFBuildingResponse
DOI: 10.5281/zenodo.10993603
title: E2MDOFBuildingResponse
DOI: 10.5281/zenodo.11089144
title: E2MDOFBuildingResponse
DOI: 10.5281/zenodo.14782348
title: E2MDOFBuildingResponse

description: This material is based upon work supported by the U.S. National Science Foundation under Grants No. 1612843 and No. 2131111. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.
DOI: 10.5281/zenodo.15447643
title: E2MDOFBuildingResponse

description: This material is based upon work supported by the U.S. National Science Foundation under Grants No. 1612843 and No. 2131111. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.
DOI: 10.5281/zenodo.15104056
title: When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations (ISCA 2025) -- Traces

description: Traces for the code artifact for the paper When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations, which will appear in ISCA 2025.
DOI: 10.5281/zenodo.15113127
title: When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations (ISCA 2025) -- Traces

description: Traces for the code artifact for the paper When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations, which will appear in ISCA 2025.
DOI: 10.5281/zenodo.15104055
title: When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations (ISCA 2025) -- Traces

description: Traces for the code artifact for the paper When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations, which will appear in ISCA 2025.
DOI: 10.5281/zenodo.15447648
title: When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations (ISCA 2025) -- Traces

description: Traces for the code artifact for the paper When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based Rowhammer Mitigations, which will appear in ISCA 2025.
DOI: 10.5281/zenodo.10960663
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Time-based Analysis on Software Vulnerability ML Detection: A Differentiated Replication"

Part 2 (Linux Dataset)

 

The zipped package includes:



Datasets that we created using our methodology and the original dataset (from [NVD Vuldeepecker](https://github.com/CGCL-codes/VulDeePecker))- retrospective test- believed_perspective test- perspective test

Pre-trained models that we generated during our evaluation (3 test results for each time point in the timeline [2011-2017]).


We also added the summarized result files (.xlsx)

1. Timeline of Datasets.xlsx

2. ML Evaluations.xlsx

and the notebook to produce the charts in the paper: Charts.ipynb

 

Please refer to 

https://zenodo.org/records/10965516 for Part 1 NVD Vuldeepecker Dataset
DOI: 10.5281/zenodo.14803487
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches"

Part 2 (LINUX Dataset)



This repository includes:



Code that contains the codes to replicate some parts of this study:a. 1_generate_datasets implements our methodology to generate the datasets.b. 2_run_models runs the ML models during the evaluation.c. 3_result_replication generates charts presented in the paper from the ML evaluation results.

Datasets that contain 2 folders:a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.



b. LINUX datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project linux.



Pretrained-models that we generated during our evaluation (3 test results for each time point in the timeline [2011-2019]).

Results of our evaluation, the folder ALL contains the overall results and other folders are results by model.



 

Please refer to the following repositories for the other datasets and pre-trained models:

- Part 1 NVD Vuldeeepecker : https://doi.org/10.5281/zenodo.8207883

- Part 3 OPENSSL : https://doi.org/10.5281/zenodo.10966117

- Part 4 POPPLER : https://doi.org/10.5281/zenodo.14713143
DOI: 10.5281/zenodo.15204601
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches"

Part 2 (LINUX Dataset)



This repository includes:



Code.zip that contains the codes to replicate some parts of this study:a. 1_generate_datasets implements our methodology to generate the datasets.b. 2_run_models runs the ML models during the evaluation.c. 3_result_replication generates charts presented in the paper from the ML evaluation results.

Datasets.zip that contain 2 folders:a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.



b. LINUX datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project linux.



Pretrained-models.zip that we generated during our evaluation (3 test results for each time point in the timeline [2011-2019]).

Results.zip of our evaluation, the folder ALL contains the overall results and other folders are results by model.





Documentations



INSTALL.pdf : how to install the codes

README.pdf: readme file

REQUIREMENTS.pdf: hardware and software requirements

STATUS.pdf : status for artifact submission

LICENSE.pdf: the license of this artifact

PAPER.pdf: the camera-ready version of the paper



 

Please refer to the following repositories for the other datasets and pre-trained models:

- Part 1 NVD Vuldeeepecker : https://doi.org/10.5281/zenodo.8207883

- Part 3 OPENSSL : https://doi.org/10.5281/zenodo.10966117

- Part 4 POPPLER : https://doi.org/10.5281/zenodo.14713143
DOI: 10.5281/zenodo.15433483
title: Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches (Replication Package Part 2: Linux dataset)

description: The Replication Package of

"Today's cat is tomorrow's dog: accounting for time-based changes in the labels of ML vulnerability detection approaches"

Part 2 (LINUX Dataset)



This repository includes:



Code.zip that contains the codes to replicate some parts of this study:a. 1_generate_datasets implements our methodology to generate the datasets.b. 2_run_models runs the ML models during the evaluation.c. 3_result_replication generates charts presented in the paper from the ML evaluation results.

Datasets.zip that contain 2 folders:a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.



b. LINUX datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project linux.



Pretrained-models.zip that we generated during our evaluation (3 test results for each time point in the timeline [2011-2019]).

Results.zip of our evaluation, the folder ALL contains the overall results and other folders are results by model.





Documentations



INSTALL.pdf : how to install the codes

README.pdf: readme file

REQUIREMENTS.pdf: hardware and software requirements

STATUS.pdf : status for artifact submission

LICENSE.pdf: the license of this artifact

PAPER.pdf: the camera-ready version of the paper


UPDATED version 4- added a GLOBAL_README.md which contains the 3 stages and how they are connected to each other- updated LineVul.ipynb: import AdamW from torch.optim instead of transformers- updated README.md in Code2Vec with the prerequisites of Java to run gradlew for astminer


 

Please refer to the following repositories for the other datasets and pre-trained models:

- Part 1 NVD Vuldeeepecker : https://doi.org/10.5281/zenodo.8207883

- Part 3 OPENSSL : https://doi.org/10.5281/zenodo.10966117

- Part 4 POPPLER : https://doi.org/10.5281/zenodo.14713143
DOI: 10.5281/zenodo.10966118
title: Time-based Analysis on Software Vulnerability ML Detection: A Differentiated Replication (Replication Package Part 3: OpenSSL dataset)

description: The Replication Package of

"Time-based Analysis on Software Vulnerability ML Detection: A Differentiated Replication"

Part 3 (OpenSSL Dataset)

 

The zipped package includes:



Datasets that we created using our methodology and the original dataset (from [NVD Vuldeepecker](https://github.com/CGCL-codes/VulDeePecker))- retrospective test- believed_perspective test- perspective test

Pre-trained models that we generated during our evaluation (3 test results for each time point in the timeline [2011-2017]).


We also added the summarized result files (.xlsx)

1. Timeline of Datasets.xlsx

2. ML Evaluations.xlsx

and the notebook to produce the charts in the paper: Charts.ipynb

 

Please refer to 

https://zenodo.org/records/10965516 for Part 1 NVD Vuldeepecker Dataset