cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/118823
title: Multiplexed data collected during research cruise AT31A using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7697888
title: Cognitive Aging and Tests of Rationality

description: The ZIP file contains all necessary code and data for reproducing the results from the paper "Cognitive Aging and Tests of Rationality." The pdf file "readme.pdf" provides a step-by-step instruction for readers to reproduce the results.
DOI: 10.6084/m9.figshare.7698215.v4
title: Table 1 Stability analysis of 111In-labeled 3-arm and 4-arm DOTA-alpha-MSH in plasma, liver, and kidney of mice by ex vivo

description: Stability analysis of <sup>111</sup>In-labeled 3-arm and 4-arm DOTA-alpha-MSH in plasma, liver, and kidney of mice by ex vivo
DOI: 10.6084/m9.figshare.7697888.v1
title: Cognitive Aging and Tests of Rationality

description: The ZIP file contains all necessary code and data for reproducing the results from the paper "Cognitive Aging and Tests of Rationality." The pdf file "readme.pdf" provides a step-by-step instruction for readers to reproduce the results.
DOI: 10.7284/118816
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AT31A using a Hawaii UHDAS instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/118817
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AT31A using a Sea-Bird SBE-911+ instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7697834
title: Locus alignments and RAxML trees

description: Individual locus alignments, RAxML "gene" trees, and ASTRAL tree.
DOI: 10.6084/m9.figshare.7697828
title: Sundin et al. 2019 STOTEN Suppl data

description: Raw data for analyses in the paper: Behavioural alterations induced by the anxiolytic pollutant oxazepam are reversible after depuration in a freshwater fish.<br>
DOI: 10.6084/m9.figshare.7697834.v1
title: Locus alignments and RAxML trees

description: Individual locus alignments, RAxML "gene" trees, and ASTRAL tree.
DOI: 10.6084/m9.figshare.7697834.v2
title: Locus alignments and RAxML trees

description: Individual locus alignments, RAxML "gene" trees, and ASTRAL tree.
DOI: 10.7284/118815
title: Expendable Probe data collected during research cruise AT31A using a Sippican MK12 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/118814
title: Fluorometer data collected during research cruise AT31A using a WET Labs WETStar instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695929
title: Concatenated alignment, ML, and Bayesian tree

description: The concatenated alignment, resulting RAxML best tree file with bootstrap values, and Bayesian consensus tree.
DOI: 10.6084/m9.figshare.7695929.v1
title: Concatenated alignment, ML, and Bayesian tree

description: The concatenated alignment, resulting RAxML best tree file with bootstrap values, and Bayesian consensus tree.
DOI: 10.6084/m9.figshare.7697816.v1
title: Differences between the PubMed record and full-text methods section in in-vivo animal research articles

description: Large animal protocols submitted to Institutional Animal Care and Use Committees (IACUCs) are required to include searches for alternatives and address the “3Rs": <br><br>1. Refinement: use methodology and protocols that reduce pain and distress<br>2. Replacement: substitute animals with non-animal models or lower species<br>3. Reduction: minimize the number of animals <br>Locating descriptions of methodology for the refinement concept is challenging since PubMed (and most other databases) do not search full-text. <br>The objectives of this study were to determine how well the title, abstract, and MeSH terms cover the content of the methods section in in-vivo animal research articles, particularly with respect to procedures, drugs, and animal species used, and to describe how this might impact a search.<br>The title/abstract, MeSH terms, and methods section of each article were reviewed and details such as: animal species, number of animals, description of housing, description of experimental procedures used, and analgesia/anesthesia were extracted. <br><br>Articles were screened from April 2017 - September 2017. <br><br>Details for the methodology used and description of uploaded files are provided in the README.txt file. <br>
DOI: 10.7284/118813
title: GNSS (Global Navigation Satellite System) data collected during research cruise AT31A using a C&C C-Nav 2050G instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695833
title: HepE vaccination stakeholder study

description: Attached is a list of questions asked as part of a study on Hepatitis E
DOI: 10.6084/m9.figshare.7695857
title: Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A

description: These are the original figures of an article entitled as "Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A."
DOI: 10.7284/118819
title: Meteorological Station data collected during research cruise AT31A using a Vaisala WXT520 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/118820
title: Meteorological Station data collected during research cruise AT31A using a Vaisala WXT520 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695710
title: Ptomacanthus scan parameters

description: Scan parameters of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695701
title: Ptomacanthus stack part 4

description: The fourth 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695857.v3
title: Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A

description: These are the original figures of an article entitled as "Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A."
DOI: 10.6084/m9.figshare.7695710.v1
title: Ptomacanthus scan parameters

description: Scan parameters of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695857.v2
title: Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A

description: These are the original figures of an article entitled as "Voluntary wheel running activates Akt/AMPK/eNOS signaling cascades without improving profound endothelial dysfunction in mice deficient in α-galactosidase A."
DOI: 10.7284/118818
title: Multibeam Echosounder data collected during research cruise AT31A using a Kongsberg EM122 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695698
title: Ptomacanthus stack part 3

description: The third 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695701.v1
title: Ptomacanthus stack part 4

description: The fourth 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695662
title: GPR dataset acquired around the 2014 margin of Norway's Midtdalsbreen glacier

description: This archive contains raw ground-penetrating radar data from around the margins of Norway's Midtdalsbreen glacier, acquired in spring 2014. The data are archived in support of the paper "Pervasive cold-ice within a temperate glacier - implications for glacier thermal regime, sediment transport and foreland geomorphology", published in The Cryosphere in 2019 by Reinardy <i>et al</i>..<br>All data were acquired with a Mala 50 MHz Rough Terrain Antenna. Each data file is fully documented in the supporting information, and contains the necessary header and positional information both to replicate and develop the analysis performed. <br>For any information about the data, and advice about using it, please contact Adam Booth at the University of Leeds (a.d.booth@leeds.ac.uk).
DOI: 10.6084/m9.figshare.7695698.v1
title: Ptomacanthus stack part 3

description: The third 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.7284/118821
title: Radiometer data collected during research cruise AT31A using a Eppley PIR instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695620
title: Genetic Tagging- Lamb et al. 2019 Eco Apps

description: Data and script for analyzing genetic capture recapture data as shown in Lamb et al. 2019 Eco Apps.
DOI: 10.7284/118822
title: Radiometer data collected during research cruise AT31A using a Eppley PSP instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695617
title: Supplementary Tables

description: Supplementary Tables containing PCR primers, antibodies and Accession numbers.
DOI: 10.6084/m9.figshare.7695605
title: Ptomacanthus stack part 2

description: The second 500 slices of a CT scan of<i> Ptomacanthus anglicus </i>specimen<i> </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695617.v1
title: Supplementary Tables

description: Supplementary Tables containing PCR primers, antibodies and Accession numbers.
DOI: 10.7284/118833
title: Multiplexed data collected during research cruise AT31B using a WHOI Calliope instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695596
title: Table S6. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Rare Earth Element (REE) and minor element ICP-MS analyses of comparative felsic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite, and also from the Otama Complex.
DOI: 10.6084/m9.figshare.7695599
title: Table S3. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of comparative basic extrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite and also from the Otama Complex.
DOI: 10.6084/m9.figshare.7695605.v1
title: Ptomacanthus stack part 2

description: The second 500 slices of a CT scan of<i> Ptomacanthus anglicus </i>specimen<i> </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695620.v1
title: Genetic Tagging- Lamb et al. 2019 Eco Apps

description: Data and script for analyzing genetic capture recapture data as shown in Lamb et al. 2019 Eco Apps.
DOI: 10.6084/m9.figshare.7695593
title: Table S4. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Rare Earth Element (REE) and minor element ICP-MS analyses of basic-composition clasts from the Upukerora Formation and comparable basic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite and the Otama Complex.
DOI: 10.6084/m9.figshare.7695596.v1
title: Table S6. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Rare Earth Element (REE) and minor element ICP-MS analyses of comparative felsic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite, and also from the Otama Complex.
DOI: 10.6084/m9.figshare.7695599.v1
title: Table S3. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of comparative basic extrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite and also from the Otama Complex.
DOI: 10.7284/118826
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AT31B using a Hawaii UHDAS instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695593.v1
title: Table S4. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Rare Earth Element (REE) and minor element ICP-MS analyses of basic-composition clasts from the Upukerora Formation and comparable basic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite and the Otama Complex.
DOI: 10.6084/m9.figshare.7695587
title: Table S5. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of comparative felsic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite, and also from the Otama Complex.
DOI: 10.6084/m9.figshare.7695590
title: Table S1. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Point-count data for relatively unaltered medium-grained sandstone making up the matrix of the Permian Upukerora Formation, compared with sandstones from the overlying Wooded Peak Formation.
DOI: 10.6084/m9.figshare.7695620.v4
title: Genetic Tagging- Lamb et al. 2019 Eco Apps

description: Data and script for analyzing genetic capture recapture data as shown in Lamb et al. 2019 Eco Apps.
DOI: 10.6084/m9.figshare.7695584
title: Table S2. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of basic-composition clasts from the Upukerora Formation.
DOI: 10.6084/m9.figshare.7695587.v1
title: Table S5. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of comparative felsic extrusive and intrusive igneous rocks from the uppermost levels of the Dun Mountain Ophiolite, and also from the Otama Complex.
DOI: 10.6084/m9.figshare.7695590.v1
title: Table S1. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Point-count data for relatively unaltered medium-grained sandstone making up the matrix of the Permian Upukerora Formation, compared with sandstones from the overlying Wooded Peak Formation.
DOI: 10.7284/118827
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AT31B using a Sea-Bird SBE-911+ instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695620.v3
title: Genetic Tagging- Lamb et al. 2019 Eco Apps

description: Data and script for analyzing genetic capture recapture data as shown in Lamb et al. 2019 Eco Apps.
DOI: 10.6084/m9.figshare.7695560
title: Ptomacanthus stack part 1

description: The first 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695584.v1
title: Table S2. Mid–Late Permian Upukerora Formation, South Island, New Zealand: fault-controlled mass wasting of the Early Permian Dun Mountain Ophiolite and initiation of the Permian–Triassic Maitai continental margin forearc basin

description: Major and trace element XRF analyses of basic-composition clasts from the Upukerora Formation.
DOI: 10.7284/118825
title: Fluorometer data collected during research cruise AT31B using a WET Labs WETStar instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695545
title: Case_report_data.xlsx

description: False-negative result of serum cryptococcal antigen lateral flow assay in an HIV-infected patient with culture-proven cryptococcemia<b> </b>
DOI: 10.6084/m9.figshare.7695554
title: Comparing Machine Learning and Heuristic Approaches for Metric-Based Code Smell Detection

description: Code smells represent poor implementation choices applied by developers when enhancing source code. Their negative impact on source code maintainability and comprehensibility has been widely shown in the past and several techniques to automatically detect them have been devised. Most of these techniques are based on heuristics, namely they compute a set of code metrics and combine them by creating detection rules; while they have a reasonable accuracy, a recent trend is represented by the use of machine learning where code metrics are used as predictors of the smelliness of code artifacts. Despite the recent advances in the field, there is still a noticeable lack of knowledge of whether machine learning can actually be more accurate than traditional heuristic-based approaches. To fill this gap, in this paper we propose a large-scale study to empirically compare the performance of heuristic-based and machine-learning-based techniques for metric-based code smell detection. We consider six code smell types and compare machine learning models with Decor, a state-of-the-art heuristic-based approach. Key findings emphasise the need of further research aimed at improving the effectiveness of machine learning to code smell detection. Indeed, on the one hand​, machine-learning-based-techniques generally achieve better performance without requiring any threshold definitions, while on the other hand for some specific code smell types sometimes the training data are not enough to make the models able to discriminate the smelliness of code components.
DOI: 10.6084/m9.figshare.7695560.v1
title: Ptomacanthus stack part 1

description: The first 500 slices of a CT scan of<i> Ptomacanthus anglicus specimen </i>P24919a (Natural History Museum, London), scanned at University of Bristol, Life Sciences Department
DOI: 10.6084/m9.figshare.7695533
title: start.ipynb

description: Sample Python notebook
DOI: 10.7284/118824
title: GNSS (Global Navigation Satellite System) data collected during research cruise AT31B using a C&C C-Nav 2050G instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695530
title: raw data_high-temperature properties

description: High-temperature properties with different alloying elements in Cr hot-work tool steels
DOI: 10.6084/m9.figshare.7695533.v1
title: start.ipynb

description: Sample Python notebook
DOI: 10.6084/m9.figshare.7695545.v2
title: Case_report_data.xlsx

description: False-negative result of serum cryptococcal antigen lateral flow assay in an HIV-infected patient with culture-proven cryptococcemia<b> </b>
DOI: 10.6084/m9.figshare.7695554.v1
title: Comparing Machine Learning and Heuristic Approaches for Metric-Based Code Smell Detection

description: Code smells represent poor implementation choices applied by developers when enhancing source code. Their negative impact on source code maintainability and comprehensibility has been widely shown in the past and several techniques to automatically detect them have been devised. Most of these techniques are based on heuristics, namely they compute a set of code metrics and combine them by creating detection rules; while they have a reasonable accuracy, a recent trend is represented by the use of machine learning where code metrics are used as predictors of the smelliness of code artifacts. Despite the recent advances in the field, there is still a noticeable lack of knowledge of whether machine learning can actually be more accurate than traditional heuristic-based approaches. To fill this gap, in this paper we propose a large-scale study to empirically compare the performance of heuristic-based and machine-learning-based techniques for metric-based code smell detection. We consider six code smell types and compare machine learning models with Decor, a state-of-the-art heuristic-based approach. Key findings emphasise the need of further research aimed at improving the effectiveness of machine learning to code smell detection. Indeed, on the one hand​, machine-learning-based-techniques generally achieve better performance without requiring any threshold definitions, while on the other hand for some specific code smell types sometimes the training data are not enough to make the models able to discriminate the smelliness of code components.
DOI: 10.6084/m9.figshare.7695545.v1
title: Case_report_data.xlsx

description: False-negative antigenemia by LFA in HIV patient
DOI: 10.6084/m9.figshare.7695515
title: AAS 27 data.xlsx

description: Artefactual data accompanying the monograph 'The Roman object revolution. Objectscapes and intra-cultural connectivity in northwest Europe' (Amsterdam Archaeological Studies 27, 2019), by Martin Pitts.
DOI: 10.6084/m9.figshare.7695515.v1
title: AAS 27 data.xlsx

description: Artefactual data accompanying the monograph 'The Roman object revolution. Objectscapes and intra-cultural connectivity in northwest Europe' (Amsterdam Archaeological Studies 27, 2019), by Martin Pitts.
DOI: 10.7284/118829
title: Meteorological Station data collected during research cruise AT31B using a Vaisala WXT520 instrument system onboard the platform RV Atlantis

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.7695497
title: Primers for ChIP PCR

description: Primers for ChIP PCR