cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vsg8rs
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leptospermum recurvum Hook.fil."
 ]
}

 The dataset includes 120 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043284-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y3xmat
title: Occurrence Download

description: A dataset containing 124388 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lilium martagon L."
 ]
}

 The dataset includes 124388 records from 806 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043259-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15139/s3/j8dmer
title: Sources of Strength - Implementation

description: Data are from a cluster randomized trial of the Sources of Strength program in 20 high schools. The intervention condition contained 11 high schools and the waitlist control condition contained 9 high schools. Sources of Strength (https://sourcesofstrength.org/) is a universal preventive intervention that prepares student opinion leaders (called Peer Leaders [PL]) to modify social-ecological protective factors, including healthy bonds to adults, within their schools and social networks. The Sources program involves three phases: (1) School and community preparation, (2) PL recruitment and training, and (3) School-wide prevention campaigns. The Implementation dataset contains quantitative information regarding the implementation of these three phases in the 11 intervention schools across four data collection points (Fall 2017 – Spring 2019).
DOI: 10.15139/s3/lyspt9
title: Sources of Strength - School Climate Survey

description: Data are from a cluster randomized trial of the Sources of Strength program in 20 high schools. The intervention condition contained 11 high schools and the waitlist control condition contained 9 high schools. Sources of Strength (https://sourcesofstrength.org/) is a universal preventive intervention that prepares student opinion leaders (called Peer Leaders [PL]) to modify social-ecological protective factors, including healthy bonds to adults, within their schools and social networks. The Sources program involves three phases: (1) School and community preparation, (2) PL recruitment and training, and (3) School-wide prevention campaigns. The School Climate Survey dataset contains responses from 2676 teachers, administrators, and staff in 20 schools across four data collection points (Fall 2017 – Spring 2019).
DOI: 10.15139/s3/ez8ilc
title: Sources of Strength - Student Survey

description: Data are from a cluster randomized trial of the Sources of Strength program in 20 high schools. The intervention condition contained 11 high schools and the waitlist control condition contained 9 high schools. Sources of Strength (https://sourcesofstrength.org/) is a universal preventive intervention that prepares student opinion leaders (called Peer Leaders [PL]) to modify social-ecological protective factors, including healthy bonds to adults, within their schools and social networks. The Sources program involves three phases: (1) School and community preparation, (2) PL recruitment and training, and (3) School-wide prevention campaigns. The Student Survey dataset contains responses from 6465 9th-11th grade students across 4 data collection waves (Fall 2017 – Spring 2019). Data collection occurred once each semester during regular class times under the supervision of two researchers. Most surveys were completed online in English while an online and paper version was also available in Spanish. A braille version was also used in one school. This codebook provides a list and description of the original and transformed variables in the dataset.
DOI: 10.6073/pasta/6e65d6c6e60e5722ec2c24bc60e63957
title: High-frequency water quality and air parameters from large lake Võrtsjärv, Estonia: 2010-2019

description: This high frequency water-air dataset was collected from large shallow Lake Võrtsjärv (Estonia) with an automated lake monitoring buoy system and was used in the analyses described in the manuscript by Thayne, M.W., B. Kraemer, J.P. Mesman, A. Laas, E. de Eyto, B. W. Ibelings, R. Adrian. “Trophic state effects on antecedent lake characteristics shape the resistance and resilience of lakes following extreme storms”. Dataset contains every 10-minute measurements from the open water periods in years 2010-2019. Underwater measurements were conducted with Yellow Springs Instrument multiparameter sonde model YSI 6600 V2-4. Underwater measurements contain the collected values of pH, dissolved oxygen, dissolved oxygen saturation, water temperature, specific conductance, water turbidity, chlorophyll concentration (calculated by the sensor from fluorescence values), and the abundance of the bluegreen algae (calculated by the sensor from phycocyanin fluorescence values). Air parameters were collected with the Vaisala multiparameter weather station model WXT520 and contain measurements of wind direction, wind speed, air temperature, atmospheric pressure, and cumulative amount of rain between measurement periods. All air measurements were collected 2 m above from the water surface. Additionally, solar irradiance measurements were collected from the automated buoy system with the Licor pyranometer model LI-200, those measurements contain values in two different columns: average solar irradiance in W/m2 and average photon flux density values in micromoles per square meter per second.
DOI: 10.6084/m9.figshare.23620479.v3
title: Data Repository

description: Raw data products from Widespread Presense of Endogenized Polintoviruses in Scleretina Coral Genomes
DOI: 10.6084/m9.figshare.23620479.v4
title: Data Repository

description: Raw data products from Widespread Presense of Endogenized Polintoviruses in Scleretina Coral Genomes
DOI: 10.6084/m9.figshare.23906160
title: JNs_Endorse_Guidelines.zip

description: Journals endorsed biomedical reporting guidelines. Three files for the manuscript under review.
DOI: 10.6084/m9.figshare.23906160.v1
title: JNs_Endorse_Guidelines.zip

description: Journals endorsed biomedical reporting guidelines. Three files for the manuscript under review.
DOI: 10.5519/qd.e1xofm91
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (27 records)
DOI: 10.6073/pasta/eaea9a699715c708b71a599a052905fa
title: El Yunque National Forest Vegetation Monitoring Project data, 2019-2021

description: This data package includes data collected as part of the El Yunque National Forest (EYNF) Vegetation Monitoring Project, the first phase of which was conducted between January 2019 and April 2021 and is now completed. EYNF is coterminous with the Luquillo Experimental Forest. The project was implemented as a collaborative endeavor between the Amigos de El Yunque Foundation, the USDA Forest Service, and the University of Puerto Rico-Río Piedras Campus. Funding was provided by the Forest Service. It includes data for 40 0.1-ha circular plots located in secondary forest within the subtropical moist and wet life zones, ranging in elevation from approximately 100-600 m asl. Plots are classified into three groups based on combinations of their historical canopy cover and post-agricultural regeneration pathways. The first group corresponds to secondary forest plots with &gt;50% canopy cover in 1936 that have continued to recover via passive natural regeneration (&gt;50 P plots). The second group corresponds to secondary forest plots with &lt;50% canopy cover in 1936 that have continued to recover via passive natural regeneration (&lt;50 P plots). The third group corresponds to secondary forest plots that also had &lt;50% cover in 1936 and experienced a combination of both assisted and passive natural regeneration (50 A+P plots). The assisted regeneration occurred up to the early 1980s. Since the 1980s this third group of plots has only undergone exclusively passive natural restoration. Eleven plots (total area = 1.1 ha) are classified as &gt;50 P, 21 plots (total area = 2.1 ha) are classified as &lt;50 P, and 8 plots (total area = 0.8 ha) as &lt;50 A+P. There are two data sets. The first represents general plot and ground cover data for the 40 plots. The second represents tree composition, structure, biomass, and ecosystem service data for 4242 trees within the 40 plots. Data were collected using i-Tree Eco methodology.
DOI: 10.6073/pasta/9f8fb5bb7ce3d9549e2cab219fdc65d8
title: Marcell Experimental Forest chemistry of surface water draining the S6 catchment, 1986 - ongoing

description: This data set is a record since 1986 of chemistry for surface water draining the S6 catchment at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. Unfiltered water is usually collected every one or two weeks as part of the long-term monitoring program of the S6 catchment. Some samples were collected more often for various other studies and are included in this data set. Samples are routinely measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, manganese, strontium), silicon, nutrients (ammonium, nitrate+nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon. Occasionally, stable water isotopes as well as concentrations of dissolved organic carbon (DOC), bacterial respiration of dissolved organic matter, biodegradable DOC (BDOC), ferrous and ferric iron, total mercury (filtered or unfiltered), and methylmercury (filtered or unfiltered) were measured. Ultraviolet (UV) absorbance, a measure of water color or dissolved organic matter optical properties, was also measured for some samples. More solutes and values will be added as additional metadata are documented (pre-1986 to 1992), water samples are collected and analyzed (concentrations and isotopes), or archived water samples are analyzed for stable water isotopes. The MEF is operated and maintained by the USDA Forest Service, Northern Research Station.
DOI: 10.6073/pasta/f6bb4f5f602060dec6652ff8eb555082
title: Time series of high-frequency sensor data measuring water temperature, dissolved oxygen, pressure, conductivity, specific conductance, total dissolved solids, chlorophyll a, phycocyanin, fluorescent dissolved organic matter, and turbidity at discrete depths in Falling Creek Reservoir, Virginia, USA in 2018-2022

description: Depth profiles of water temperature on 1m intervals from 0.1 to 9 m depth; dissolved oxygen at 5 and 9 m depth; pressure at 9 m depth; and temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, fluorescent dissolved organic matter, and pressure at ~1.6 m depth were collected with a suite of high-frequency sensors at Falling Creek Reservoir (Vinton, Virginia, USA) on the 10-minute scale in 2018-2022. Falling Creek Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. This data product consists of one dataset compiled from water temperature data measured at multiple depths by thermistors, two dissolved oxygen sensors at multiple depths, pressure measured at one depth, and a YSI EXO2 sonde that measures temperature, dissolved oxygen, pressure, conductivity, specific conductance, chlorophyll a, phycocyanin, total dissolved solids, and fluorescent dissolved organic matter, at one depth, all measured at the deepest site of the reservoir adjacent to the dam.
DOI: 10.6084/m9.figshare.23792385.v3
title: Extended data- Example of participants' responses (NSG)

description: This is part of the extended data for the article entitled "L2 Acquisition of <i>Wh-</i>interrogatives at the Syntax-discourse Interface: Interface Hypothesis again", by Mohammed Shormani
DOI: 10.6084/m9.figshare.23792382.v4
title: Extended data- Example of participants' responses (AVG)

description: This is part of the extended data for the article entitled "L2 Acquisition of <i>Wh-</i>interrogatives at the Syntax-discourse Interface: Interface Hypothesis again", by Mohammed Shormani
DOI: 10.5517/ccdc.csd.cc2fr0qy
title: CCDC 2256450: Experimental Crystal Structure Determination

description: Related Article: Bojidarka Ivanova|2023|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: 10.5517/ccdc.csd.cc2fr0rz
title: CCDC 2256451: Experimental Crystal Structure Determination

description: Related Article: Bojidarka Ivanova|2023|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: 10.5517/ccdc.csd.cc2fr0px
title: CCDC 2256449: Experimental Crystal Structure Determination

description: Related Article: Bojidarka Ivanova|2023|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: 10.5517/ccdc.csd.cc2frd9x
title: CCDC 2256809: Experimental Crystal Structure Determination

description: Related Article: D SAJAN|2023|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: 10.5517/ccdc.csd.cc2fr55k
title: CCDC 2256588: Experimental Crystal Structure Determination

description: Related Article: CHENGJUN JIANG|2023|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: 10.5517/ccdc.csd.cc2frbfz
title: CCDC 2256751: Experimental Crystal Structure Determination

description: Related Article: John D. Wallis, Arjun G. Pankhania|2023|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: 10.5517/ccdc.csd.cc2frc6s
title: CCDC 2256775: Experimental Crystal Structure Determination

description: Related Article: Ze-Jiu Diao, Guan-Zhou Wu, Tian-Jing Zhang, Hang-Ou Qi, Jing-Jing Li, Ming Lu, Guoliang Liu, Xiao-Qin Liu, Lin-Bing Sun|2023|J.Mater.Chem.A|11|16293|doi:10.1039/D3TA02467A
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.cc2dch1b
title: CCDC 2215571: Experimental Crystal Structure Determination

description: Related Article: Yunfeng Du, Yuefei Liu, Hongyu Guo, Rongfang Liu, Rong Zhou|2023|Org.Lett.|25|4776|doi:10.1021/acs.orglett.3c01348
description: Related Article: DU YUNFENG|2023|CSD Communication|||
description: Related Article: DU YUNFENG|2023|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: 10.5517/ccdc.csd.cc2frjnd
title: CCDC 2256944: Experimental Crystal Structure Determination

description: Related Article: yang yongcheng|2023|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: 10.5517/ccdc.csd.cc2frk3w
title: CCDC 2256958: Experimental Crystal Structure Determination

description: Related Article: Mikko Hänninen, Reijo Sillanpää|2023|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: 10.5517/ccdc.csd.cc2frk70
title: CCDC 2256962: Experimental Crystal Structure Determination

description: Related Article: Brian Jameson, Emilie Overschmidt, Steven P. Kelley, Rainer Glaser|2023|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: 10.5517/ccdc.csd.cc2frwlp
title: CCDC 2257283: Experimental Crystal Structure Determination

description: Related Article: Wenhao Yan, Jeanette A. Krause|2023|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: 10.6084/m9.figshare.23792277.v3
title: Extended data-Example of participants' responses (IMG)

description: This is part of the extended data for the article entitled "L2 Acquisition of <i>Wh-</i>interrogatives at the Syntax-discourse Interface: Interface Hypothesis again", by Mohammed Shormani
DOI: 10.6084/m9.figshare.23792277.v4
title: Extended data-Example of participants' responses Intermediate Learner Group (IMG)

description: This is part of the extended data for the article entitled "L2 Acquisition of <i>Wh-</i>interrogatives at the Syntax-discourse Interface: Interface Hypothesis again", by Mohammed Shormani
DOI: 10.5281/zenodo.7085984
title: Urine NMR metabolomics for precision oncology in colorectal cancer

description: Tables summarizing the data used for the review. Up to 7 tables, and a list of the included studies is provided.
DOI: 10.5281/zenodo.7044969
title: Urine NMR metabolomics for precision oncology in colorectal cancer

description: Tables summarizing the data used for the review. Up to 7 tables, and a list of the included studies is provided.
DOI: 10.5281/zenodo.7872811
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: pretrained models of Sei (PMID: 35817977) + our 3D structure embedding models are shared. The models are trained and validated using DeepSEA (PMID: 26301843) selected 200 bp regions (we extended to 4K bp neighboring) to predict the epigenetic profile containing 21907 epigenetic events Sei processed.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.5281/zenodo.7976389
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: pretrained models of Sei (PMID: 35817977) + our 3D structure embedding models are shared. The models are trained and validated using DeepSEA (PMID: 26301843) selected 200 bp regions (we extended to 4K bp neighboring) to predict the epigenetic profile containing 21907 epigenetic events Sei processed. The pretrained DeepSEA (PMID: 26301843) and reproduced DanQ (PMID: 27084946) can be found in SOTA.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.5281/zenodo.8077445
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: pretrained models of Sei (PMID: 35817977) + our 3D structure embedding models are shared. The models are trained and validated using DeepSEA (PMID: 26301843) selected 200 bp regions (we extended to 4K bp neighboring) to predict the epigenetic profile containing 21907 epigenetic events Sei processed. The pretrained DeepSEA (PMID: 26301843) and reproduced DanQ (PMID: 27084946) can be found in SOTA.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}
DOI: 10.6084/m9.figshare.23792208.v5
title: Underlying data- total results

description: This is the underlying data for the article entitled "L2 Acquisition of <i>Wh-</i>interrogatives at the Syntax-discourse Interface: Interface Hypothesis again", by Mohammed Shormani
DOI: 10.5281/zenodo.7872810
title: Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

description: ncVarPred-1D3D: pretrained models of Sei (PMID: 35817977) + our 3D structure embedding models are shared. The models are trained and validated using DeepSEA (PMID: 26301843) selected 200 bp regions (we extended to 4K bp neighboring) to predict the epigenetic profile containing 21907 epigenetic events Sei processed. The pretrained DeepSEA (PMID: 26301843) and reproduced DanQ (PMID: 27084946) can be found in SOTA.tar.gz.
description: {"references": ["Tan, Wuwei, and Yang Shen. \"Multimodal learning of noncoding variant effects using genome sequence and chromatin structure.\" bioRxiv (2022): 2022-12."]}