cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7312046
title: The English Headline Treebank corpus

description: This repository contains the evaluation sets used in <pre><code>A Benton, T Shi, O İrsoy, and I Malioutov."Weakly Supervised Headline Dependency Parsing". Findings of EMNLP. 2022. </code></pre> This dataset contains parse annotations for English news headlines and a script to produce conllu files joined with original headline text. Parse annotations are joined to the corresponding text by running: <pre> LDC_NYT_DIR="/PATH/TO/UNTARRED/LDC2008T19/" # path to untarred LDC2008T19 python build_eht.py --nyt_dir ${LDC_NYT_DIR} --num_proc 4</pre> This will download the Google sentence compression (GSC) dataset, and build conllu files for GSC examples. If you have the New York Times Annotated Corpus (LDC2008T19) untarred locally, this will also join annotations to the NYT examples (location passed via <code>--nyt_dir</code>). Increase the argument to <code>--num_procs</code> to process more shards from the NYT corpus in parallel and reduce build time. The above was tested with python 3.9.7. The EHT evaluation sets, with gold-annotated POS tags and dependency relations, are built as <code>EHT/gsc.test.conllu</code> and <code>EHT/nyt.test.conllu</code> Silver, projected, trees which we used to train and validate out models are built under <code>GSC_projected</code>. These are not gold parse trees (projected predictions from the article lead sentence), and are shared purely for reproducibility sake.
description: {"references": ["Weakly Supervised Headline Dependency Parsing. Adrian Benton, Tianze Shi,Ozan Irsoy,Igor Malioutov. Findings of EMNLP 2022."]}
DOI: 10.5281/zenodo.7312045
title: The English Headline Treebank corpus

description: This repository contains the evaluation sets used in <pre><code>A Benton, T Shi, O İrsoy, and I Malioutov."Weakly Supervised Headline Dependency Parsing". Findings of EMNLP. 2022. </code></pre> This dataset contains parse annotations for English news headlines and a script to produce conllu files joined with original headline text. Parse annotations are joined to the corresponding text by running: <pre> LDC_NYT_DIR="/PATH/TO/UNTARRED/LDC2008T19/" # path to untarred LDC2008T19 python build_eht.py --nyt_dir ${LDC_NYT_DIR} --num_proc 4</pre> This will download the Google sentence compression (GSC) dataset, and build conllu files for GSC examples. If you have the New York Times Annotated Corpus (LDC2008T19) untarred locally, this will also join annotations to the NYT examples (location passed via <code>--nyt_dir</code>). Increase the argument to <code>--num_procs</code> to process more shards from the NYT corpus in parallel and reduce build time. The above was tested with python 3.9.7. The EHT evaluation sets, with gold-annotated POS tags and dependency relations, are built as <code>EHT/gsc.test.conllu</code> and <code>EHT/nyt.test.conllu</code> Silver, projected, trees which we used to train and validate out models are built under <code>GSC_projected</code>. These are not gold parse trees (projected predictions from the article lead sentence), and are shared purely for reproducibility sake.
description: {"references": ["Weakly Supervised Headline Dependency Parsing. Adrian Benton, Tianze Shi,Ozan Irsoy,Igor Malioutov. Findings of EMNLP 2022."]}
DOI: 10.7924/r40p1770c
title: Photographs from: Fire prevention and natural reforestation of grasslands in the Ngogo area of Kibale National Park, Uganda (1976-2018)

description: Photographs were taken from the top of Ngogo Hill (~ 0 degrees 30' N., 30 degrees 25.5' E.)  in what is now the Kibale National Park at irregular intervals between 1976 and 2018 with the intent of demonstrating habitat changes over time. When the first photos were taken in the 1970s, Ngogo Hill and much of the surrounding area was grassland with isolated trees and shrubs here and there. These grasslands were, in a sense, islands within an area largely dominated by tropical rain forest. Lang Brown and Happold (1962) concluded that these grasslands in Kibale were anthropogenic, the consequence of past cultivation and fire. Prior to the early 1900s, Kibale was inhabited by people until it became infested with tsetse fly. In 1932 the Kibale Forest was formally declared a Crown Forest by the Government of Uganda and occupation by humans was prohibited. Subsequent to this, the grasslands continued to be burned by hunters. When a research camp was established near Ngogo Hill in 1974, every attempt was made to prevent poaching and burning of these grasslands. As protection became more effective, the grasslands were slowly colonized by shrubs and trees. The images archived here demonstrate some of these changes and establish a baseline for continued long-term research on forest regeneration. The images also demonstrate the importance of fire prevention as an effective approach to forest restoration, which in turn leads to increases in populations of forest dependent species, such as chimpanzees and other primates.

See Lwanga (2003) and Struhsaker (1975 and 1997) for basic ecological details for Kibale and Ngogo.
DOI: 10.12751/g-node.8zwmk4
title: “Look straight ahead” ‒ A new test to diagnose spatial neglect by computed tomography

description: We measured the conjugated eye deviation (CED) on the initial computed tomography (CT) scans, in combination with the verbal instruction “Please look straight ahead” during the scan. The command was implemented in the scanner program and automatically played before a cranial CT started. This prospective study included a total 46 consecutive subjects (16 patients with first ever right brain damage and no spatial neglect, 12 patients with first ever right brain damage and spatial neglect, and 18 healthy controls). The right brain damaged groups were submitted to paper pencil tests to access the diagnosis of a spatial neglect after radiological confirmation of the brain damage during the initial phase of their hospitalisation. This procedure allowed us to define a cut-off value of 14.1 degrees of CED to the ipsilesional side to differentiate right hemispheric stroke patients with versus without spatial neglect with a confidence interval of 99%.
description: IsSupplementTo: Marques JC, Hanke J, Schell C, Andres F, Karnath H-O (2022) “Look straight ahead” – A new test to diagnose spatial neglect by computed tomography. medRxiv 2022.08.22.22278887. (https://doi.org/10.1101/2022.08.22.22278887)
DOI: 10.18112/openneuro.ds004288.v1.0.2
title: Open Access Series of Imaging Studies Subset (AFIDs-OASIS)
DOI: 10.18112/openneuro.ds004253.v1.0.3
title: HCP Unrelated 100 Subset (HCP-30)
DOI: 10.18112/openneuro.ds004298.v1.0.1
title: London Heath Sciences Center Parkinson's Disease Dataset (PD-40)
DOI: 10.5281/zenodo.7262587
title: Perceived water-related risk factors of Buruli ulcer in two villages of south-central Côte d'Ivoire

description: Metadata describing the details of the underlying data (i.e. transcripts and notes of interviews, kml-files and pictures).
DOI: 10.5281/zenodo.7262588
title: Perceived water-related risk factors of Buruli ulcer in two villages of south-central Côte d'Ivoire

description: Metadata describing the details of the underlying data (i.e. transcripts and notes of interviews, kml-files and pictures).
DOI: 10.5281/zenodo.7314078
title: Perceived water-related risk factors of Buruli ulcer in two villages of south-central Côte d'Ivoire

description: Metadata describing the details of the underlying data (i.e. transcripts and notes of interviews, kml-files and pictures).
DOI: 10.34740/kaggle/dsv/4490097
title: Cristiano Ronaldo | All Club Goals
DOI: 10.6084/m9.figshare.21541536
title: X_features.csv

description: X input features. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6084/m9.figshare.21541536.v1
title: X_features.csv

description: X input features. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6084/m9.figshare.21543120
title: Y_categories.csv

description: Output categories. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6084/m9.figshare.21541518.v1
title: state_county.csv

description: State & county codes. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6084/m9.figshare.21543120.v1
title: Y_categories.csv

description: Output categories. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6084/m9.figshare.21541518
title: state_county.csv

description: State & county codes. The data is sampled, simulated, and anonymized due to the privacy issues of the original data from Data Axle (https://www.data-axle.com/our-data/).
DOI: 10.6073/pasta/51eafc2bb556343ef1d1f3a957ed1b7c
title: Lake Wingra: Fish Lengths and Weights

description: Data are collected annually to enable us to track the fish assemblages of Lake Wingra. Sampling is done at six littoral zone sites per lake with a beach seine, minnow or crayfish traps, and fyke nets, while a boat-mounted electrofishing system samples four littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two nearshore sites per lake. Fish are identified to species. Lengths are measured for all fish caught, while weight and scale are collected from a subset. Derived data includes catch per unit effort and size distribution by species, lake, and year. Sampling Frequency: annually. Number of sites: 1. Note that 2020 data does not exist due to insufficient sampling.
DOI: 10.18112/openneuro.ds004241.v1.0.2
title: Stereotactic Neurosurgery 7T Control Dataset (SNSX)
DOI: 10.6073/pasta/5b5afcd37e57acc86a896e0f9abc381c
title: Lake Wingra: Fish Abundance 1995 - current

description: Data are collected annually to enable us to track the fish assemblages of Lake Wingra. Sampling is done at six littoral zone sites per lake with a beach seine, minnow or crayfish traps, and fyke nets, while a boat-mounted electrofishing system samples four littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two nearshore sites per lake. Fish are identified to species. Lengths are measured for all fish caught, while weight and scale are collected from a subset. Derived data include catch per unit effort and size distribution by species, lake, and year. Protocol used to generate data: Number caught for each species is summed over repetitions of a gear within a lake and over depth. Sampling Frequency: annually. Number of sites: 1. Note that 2020 data does not exist due to insufficient sampling.
DOI: 10.5281/zenodo.7312039
title: Electronic correlations and universal long-range scaling in kagome metals

description: Dataset for the constrained Random Phase Approximation calculations shown in the manuscript. The VASP OUTCAR (ascii plain texy file) contains the whole cRPA U_iijj, U_ijij and U_ijji tensors, from which the numbers in the table of the paper (Supplementary Material) are extracted. Input files necessary to reproduce the results are also in the repository.
DOI: 10.5281/zenodo.7312038
title: Electronic correlations and universal long-range scaling in kagome metals

description: Dataset for the constrained Random Phase Approximation calculations shown in the manuscript. The VASP OUTCAR (ascii plain texy file) contains the whole cRPA U_iijj, U_ijij and U_ijji tensors, from which the numbers in the table of the paper (Supplementary Material) are extracted. Input files necessary to reproduce the results are also in the repository.
DOI: 10.6073/pasta/60b19ba4306e41bd25daa6c073b2eb74
title: North Temperate Lakes LTER: Fish Species Richness 1981 - current

description: This data set is a derived data set based on fish catch data. Data are collected annually to enable us to track the fish assemblages of eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, bog lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra and Fish). Sampling on Lakes Monona, Wingra, and Fish started in 1995; sampling on other lakes started in 1981. Sampling is done at six littoral zone sites per lake with seine, minnow or crayfish traps, and fyke nets; a boat-mounted electrofishing system samples three littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two sites per lake. In the bog lakes only fyke nets and minnow traps are deployed. Parameters measured include species-level identification and lengths for all fish caught, and weight and scale samples from a subset. Derived data sets include species richness, catch per unit effort, and size distribution by species, lake, and year. Species richness for a lake is the number of fish species caught in that lake during the annual fish sampling. Hybrids captured are only included in the richness value if neither of the two hybridized species are caught in the lake that year. Fish identified only to genus or higher taxonomic level are not included if any fish identified to species within that genus or higher taxonomic level are caught. E.g., Unidentified Chub would be only included in the richness value if no other chub is caught in that lake that year. Sampling Frequency: annually. Number of sites: 11 Note that 2020 data does not exist due to insufficient sampling. In 2021, sampling in Fish Lake was suspended due to significant lake level changes. Please consult NTL's website for information on experimental lake manipulations and the DNR's website for management activities
DOI: 10.5281/zenodo.7255363
title: PanDDA analysis of PTP1B re-screened against fragment libraries at RT

description: PTP1B re-screened against multiple fragment libraries with RT crystallography
DOI: 10.34740/kaggle/dsv/4490116
title: Game of Thrones All Seasons Dataset
DOI: 10.5517/ccdc.csd.cc1q41gc
title: CCDC 1582812: Experimental Crystal Structure Determination

description: Related Article: Zhi-Hui Wang, Xiao-Zhong Wang, Xiao-Yong Lai, Qin Hou, Jing-Xin Ma, Jian-Hua Li, Kai Yue, Qing-Feng Yang|2020|J.Mol.Struct.|1202|127341|doi:10.1016/j.molstruc.2019.127341
description: Related Article: Zhi-Hui Wang, Xiao-Zhong Wang, Xiao-Yong Lai, Qin Hou, Jing-Xin Ma, Jian-Hua Li, Kai Yue, Qing-Feng Yang|2020|J.Mol.Struct.|1202|127341|doi:10.1016/j.molstruc.2019.127341
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.cc221g7v
title: CCDC 1908026: Experimental Crystal Structure Determination

description: Related Article: Zhi-Hui Wang, Xiao-Zhong Wang, Xiao-Yong Lai, Qin Hou, Jing-Xin Ma, Jian-Hua Li, Kai Yue, Qing-Feng Yang|2020|J.Mol.Struct.|1202|127341|doi:10.1016/j.molstruc.2019.127341
description: Related Article: Zhi-Hui Wang, Xiao-Zhong Wang, Xiao-Yong Lai, Qin Hou, Jing-Xin Ma, Jian-Hua Li, Kai Yue, Qing-Feng Yang|2020|J.Mol.Struct.|1202|127341|doi:10.1016/j.molstruc.2019.127341
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.cc25fyf0
title: CCDC 2009402: Experimental Crystal Structure Determination

description: Related Article: Zhengyi Liu, Yue Pan, Peng Zou, Hanchu Huang, Yali Chen, Yiyun Chen|2022|CSD Communication|||
description: Related Article: Zhengyi Liu, Yue Pan, Peng Zou, Hanchu Huang, Yali Chen, Yiyun Chen|2022|Org.Lett.|24|5951|doi:10.1021/acs.orglett.2c02210
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.cc28wczj
title: CCDC 2111688: Experimental Crystal Structure Determination

description: Related Article: Lan Gan|2022|CSD Communication|||
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: 10.25934/pr00007227
title: Add-on treatment for refractory focal-onset epilepsy: Individual Participant Data Network Meta-analysis

description: Epilepsy is a common neurological condition, with an estimated incidence of 49 per 100,000 and prevalence of 4 to 10 per 1000 in the developed world (WHO 2020). Between two and three per cent of the population will be given a diagnosis of epilepsy at some time in their lives, the majority of whom will go into remission. However, up to 30% will fail to respond to monotherapy, often requiring treatment with combinations of antiepileptic drugs (AEDs) (Cockerell 1995; Hauser 1993). These individuals will often experience significant adverse psychological and quality of life outcomes, due to continued and unpredictable seizures, side effects of drugs, and reduced educational and employment prospects.

This is a systematic review and individual participant data (IPD) network meta-analysis (NMA) of randomised controlled trials of add-on treatment for patients with refractory focal-onset epilepsy uncontrolled by one or more concomitant AEDs. In the majority of these trials, patients are randomised to have either active AED or placebo added to their existing AED treatment. This is in keeping with international guidelines on the development of AEDs (EMA 2018). Once a drug has confirmed efficacy and safety as an add‐on therapy, it is usually then tested as monotherapy and in other epilepsy syndromes. An IPD NMA of AEDs taken as monotherapy is the subject of a separate Cochrane review (Nevitt 2017).
DOI: 10.7303/syn44678922.1
title: dados2_nrow.xlsx
DOI: 10.7303/syn44678918.1
title: dados_estados_porCovid.xlsx
DOI: 10.57745/3hpqgi
title: Population location data_GEB_2021-08-01.tab

description: Reference - Original article data was extracted from; Kingdom - Fitness component measured on plants or animals; Habitat - Fitness component measured in terrestrial or marine habitats; Species - Species on which the fitness component was measured;Variable - type of fitness component (detailed categories); Performance - Type of fitness component (broad categories); Region - Population origin (C : central, LLM: Low Latitude Margin, HLM: High Latitude Margin); Population name - Population name; First year - Year of the first fitness component measurement; Last year- Year of the last fitness component measurement; Latitude - Latitude (°); Lat-Hemisphere - Northern vs. Sourthern hemisphere; Longitude - Longitude (°); Long_Hemisphere - Western vs. Eastern hemisphere
DOI: 10.57745/wefzbv
title: Population performace data_GEB_2021-08-01.xls

description: REFERENCE - Original article data was extracted from; REVIEW - Was the article a review article or not; YEAR - Publication year; KINGDOM - Fitness component measured on plants or animals; HABITAT - Fitness component measured in terrestrial or marine habitats; SPECIES - Species on which the fitness component was measured; VARIABLE - type of fitness component (detailed categories); FITNESS - Type of fitness component (broad categories); M.CENTER, SD.CENTER, N.CENTER - Mean (M), standard deviation (SD) and sample size (N) of the fitness component of the central populations; M.MARGIN, SD.MARGIN, N.MARGIN - Mean (M), standard deviation (SD) and sample size (N) of the fitness component of the marginal populations; MARGIN - Marginal population location (LLM: Low Latitude Margin, HLM : High Latidtude Margin); JOURNAL - Journal in which the original data was published
DOI: 10.57745/d85ddh
title: UPDATE_Population performace data_GEB_2022-11-10.csv

description: Reference - Original article data was extracted from; Kingdom - Fitness component measured on plants or animals; Habitat - Fitness component measured in terrestrial or marine habitats; Species - Species on which the fitness component was measured;Variable - type of fitness component (detailed categories); Performance - Type of fitness component (broad categories); Region - Population origin (C : central, LLM: Low Latitude Margin, HLM: High Latitude Margin); Population name - Population name; First year - Year of the first fitness component measurement; Last year- Year of the last fitness component measurement; Latitude - Latitude (°); Lat-Hemisphere - Northern vs. Sourthern hemisphere; Longitude - Longitude (°); Long_Hemisphere - Western vs. Eastern hemisphere
DOI: 10.23728/b2share.37cd26d0004b44fa9cdab48f69397729
title: Montado - Snow Cover Extent - 2019/2020

description: Sentinel-2 Snow Cover Extent for Montado e-shape site of years 2019 and 2020.
description: Details on methodology used can be found in this reference: https://doi.org/10.3390/rs13101957.
description: The final output consists of 20 m resolution raster masks in GeoTIFF format with: 0, No snow; 100, Snow; 205, Cloud; 254, No Data.
DOI: 10.5281/zenodo.7121083
title: LabChart files for example dataset used in Breathe Easy vignette

description: This dataset contains all 16 original LabChart recordings for the 16 example recordings used in the vignette that outlines usage of Breathe Easy. This is an incorrect folder and contains 3 files that should not be present. A new version of this dataset is published on our repository.
DOI: 10.5281/zenodo.7121082
title: LabChart files for example dataset used in Breathe Easy vignette

description: This dataset contains all 16 original LabChart recordings for the 16 example recordings used in the vignette that outlines usage of Breathe Easy. This is an incorrect folder and contains 3 files that should not be present. A new version of this dataset is published on our repository.
DOI: 10.5281/zenodo.7314256
title: Objective assessment of the relationship between quantified neuron morphological features and convolutional neural network image analysis

description: Relevant data for the publication titled: Objective assessment of the relationship between quantified neuron morphological features and convolutional neural network image analysis
DOI: 10.5281/zenodo.7314255
title: Objective assessment of the relationship between quantified neuron morphological features and convolutional neural network image analysis

description: Relevant data for the publication titled: Objective assessment of the relationship between quantified neuron morphological features and convolutional neural network image analysis