cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4730312
title: Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets

description: The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build chemometric models that can provide objective metrics of disease state. It is important to build robust and stable models to provide confidence to the end user. The data used to develop such models can have a variety of characteristics which can pose problems to many model-building approaches. Here we have compared the performance of two machine learning algorithms – AdaBoost and Random Forests – on a variety of non-uniform data sets. Using samples of breast cancer tissue, we devised a range of training data capable of describing the problem space. Models were constructed from these training sets and their characteristics compared. In terms of separating infrared spectra of cancerous epithelium tissue from normal-associated tissue on the tissue microarray, both AdaBoost and Random Forests algorithms were shown to give excellent classification performance (over 95% accuracy) in this study. AdaBoost models were more robust when datasets with large imbalance were provided. The outcomes of this work are a measure of classification accuracy as a function of training data available, and a clear recommendation for choice of machine learning approach.
description: These data include processed versions of raw infrared data available in a separate Zenodo document. https://doi.org/10.5281/zenodo.4986399
description: {"references": ["http://www.biomax.us/tissue-arrays/Breast/BR20832"]}
DOI: 10.5281/zenodo.4730311
title: Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets

description: The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build chemometric models that can provide objective metrics of disease state. It is important to build robust and stable models to provide confidence to the end user. The data used to develop such models can have a variety of characteristics which can pose problems to many model-building approaches. Here we have compared the performance of two machine learning algorithms – AdaBoost and Random Forests – on a variety of non-uniform data sets. Using samples of breast cancer tissue, we devised a range of training data capable of describing the problem space. Models were constructed from these training sets and their characteristics compared. In terms of separating infrared spectra of cancerous epithelium tissue from normal-associated tissue on the tissue microarray, both AdaBoost and Random Forests algorithms were shown to give excellent classification performance (over 95% accuracy) in this study. AdaBoost models were more robust when datasets with large imbalance were provided. The outcomes of this work are a measure of classification accuracy as a function of training data available, and a clear recommendation for choice of machine learning approach.
description: These data include processed versions of raw infrared data available in a separate Zenodo document. https://doi.org/10.5281/zenodo.4986399
description: {"references": ["http://www.biomax.us/tissue-arrays/Breast/BR20832"]}
DOI: 10.5519/qd.c59glngh
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (25577 records)
DOI: 10.5281/zenodo.5158551
title: Raw data: Validity of fitness trackers when worn by older adults

description: Co-authors of the dataset: Marina Dobnik <sup>2</sup> , Stefan Loefler <sup>3,4,6</sup> , Christian Hofer <sup>4</sup> and Nejc Šarabon <sup>2,5</sup> <sup>1</sup> University of Primorska, Andrej Marušič Institute, Muzejski trg 2, 6000 Koper, Slovenia; kaja.kastelic@iam.upr.si <sup>2</sup> University of Primorska, Faculty of Health Sciences, Polje 42, 6310 Izola, Slovenia; nejc.sarabon@fvz.upr.si <sup>3</sup> Physiko- & Rheumatherapie, Institute for Physical Medicine and Rehabilitation, 3100 St. Pölten, Austria; stefan.loefler@kern-reha.at <sup>4</sup> Ludwig Boltzmann Institute for Rehabilitation Research, Neugebäudeplatz 1, 3100 St. Pölten, Austria; christian.hofer@rehabilitationresearch.eu <sup>5</sup> InnoRenew CoE, Livade 6, 6310 Izola, Slovenia
DOI: 10.5281/zenodo.5158550
title: Raw data: Validity of fitness trackers when worn by older adults

description: Co-authors of the dataset: Marina Dobnik <sup>2</sup> , Stefan Loefler <sup>3,4,6</sup> , Christian Hofer <sup>4</sup> and Nejc Šarabon <sup>2,5</sup> <sup>1</sup> University of Primorska, Andrej Marušič Institute, Muzejski trg 2, 6000 Koper, Slovenia; kaja.kastelic@iam.upr.si <sup>2</sup> University of Primorska, Faculty of Health Sciences, Polje 42, 6310 Izola, Slovenia; nejc.sarabon@fvz.upr.si <sup>3</sup> Physiko- & Rheumatherapie, Institute for Physical Medicine and Rehabilitation, 3100 St. Pölten, Austria; stefan.loefler@kern-reha.at <sup>4</sup> Ludwig Boltzmann Institute for Rehabilitation Research, Neugebäudeplatz 1, 3100 St. Pölten, Austria; christian.hofer@rehabilitationresearch.eu <sup>5</sup> InnoRenew CoE, Livade 6, 6310 Izola, Slovenia
DOI: 10.5281/zenodo.5141721
title: In-network convolution in grid-shaped wired sensor networks

description: Data about the simulation of the in-network convolution in grid-shaped wired sensor networks. <br> We designed the simulation to examine the communication overhead of the technique applied on a wired sensor network at two different topologies.<br> Data include measurements of traveling time of packets and packet loss at varying of the link bitrate and kernel size.
DOI: 10.5281/zenodo.5141720
title: In-network convolution in grid-shaped wired sensor networks

description: Data about the simulation of the in-network convolution in grid-shaped wired sensor networks. <br> We designed the simulation to examine the communication overhead of the technique applied on a wired sensor network at two different topologies.<br> Data include measurements of traveling time of packets and packet loss at varying of the link bitrate and kernel size.
DOI: 10.7931/zmvz-xf30
title: Data for A History of Open Weather in New Zealand (HOWNZ) [Draft]
DOI: 10.7931/yk7g-vz81
title: Code for A History of Open Weather in New Zealand (HOWNZ) [Draft]
DOI: 10.6084/m9.figshare.16371525
title: Macrophyte Data

description: Macrophyte data collected over the course of 3 years as part of a Coarse Woody Debris study in Northern Canada.
DOI: 10.6084/m9.figshare.16357446
title: Maximum temperature (Spatial downscaling of PISCOt v1.1)

description: Gridded maximum temperature during 1981-2016 (daily) at 0.01° for Peru. This is a downscaled version of PISCOt v1.1 (https://bit.ly/3tZZ0iA).
DOI: 10.6084/m9.figshare.3761562.v1958
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.15468/q5ph87
title: Description of juvenile stages and adults of two new nothroid mites from Ecuador (Acari: Oribatida: Nothridae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kuty, Małgorzata (2007): Description of juvenile stages and adults of two new nothroid mites from Ecuador (Acari: Oribatida: Nothridae). Journal of Natural History 41 (9 - 12): 597-618, DOI: 10.1080/00222930701265126, URL: http://dx.doi.org/10.1080/00222930701265126
DOI: 10.6084/m9.figshare.14995314.v3
title: Effect of behavioural sampling methods on local and global social network metrics: A case-study of three macaque species

description: Data set and R-codes
DOI: 10.5281/zenodo.5234133
title: Aratinga nenday SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5234132
title: Aratinga nenday SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5234156
title: Zoanthus solanderi SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5234155
title: Zoanthus solanderi SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.15261804
title: Final PANGO SUPERPOSE.zhanggroupRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261795
title: Final PANGO superpose.wishartlabRAW DATA

description: RAW DATA
DOI: 10.5281/zenodo.5234231
title: Supplementary Information for Consonance-emerging Hebbian Learning neural network model predicts discreteness of musical scales and the Natural Just Intonation scale

description: <strong>The following phenomena and features are apparent in music and auditory perception in general: the discreteness of the tones in musical scales</strong> [1]<strong>, the prevalence of the tonal frequency span of one semitone (100 cents) in musical scales across cultures </strong>[1]<strong>, the list of tonal intervals ordered by consonance [2], and the musical performers’ preference of the Natural Just-Intonation scale [3] (A). However, researchers still have no agreement about the causes and the emergence of said phenomena (A). Here we show that the consonance-pattern emerging neural network model introduced in our previous study [4], predicts and yields all the said phenomena (A) with a precision of 1/100<sup>th</sup> of a semitone (1 cent). This precision is beyond the resolution of human hearing </strong>[5], [6], [7]. <strong>Since the Hebbian learning paradigm and harmonicity are the main features of our model, we propose that they are sufficient conditions for any system to yield the said phenomena (A). Therefore, they have a crucial role in processing pitch, consonance, and music perception in general. As a consequence, we additionally propose that the mentioned phenomena (A) are a balanced result of the joint workings of the Hebbian paradigm (nurture and cultural exposure) and harmonicity (auditory physics and biology).</strong>
DOI: 10.5281/zenodo.5234230
title: Supplementary Information for Consonance-emerging Hebbian Learning neural network model predicts discreteness of musical scales and the Natural Just Intonation scale

description: <strong>The following phenomena and features are apparent in music and auditory perception in general: the discreteness of the tones in musical scales</strong> [1]<strong>, the prevalence of the tonal frequency span of one semitone (100 cents) in musical scales across cultures </strong>[1]<strong>, the list of tonal intervals ordered by consonance [2], and the musical performers’ preference of the Natural Just-Intonation scale [3] (A). However, researchers still have no agreement about the causes and the emergence of said phenomena (A). Here we show that the consonance-pattern emerging neural network model introduced in our previous study [4], predicts and yields all the said phenomena (A) with a precision of 1/100<sup>th</sup> of a semitone (1 cent). This precision is beyond the resolution of human hearing </strong>[5], [6], [7]. <strong>Since the Hebbian learning paradigm and harmonicity are the main features of our model, we propose that they are sufficient conditions for any system to yield the said phenomena (A). Therefore, they have a crucial role in processing pitch, consonance, and music perception in general. As a consequence, we additionally propose that the mentioned phenomena (A) are a balanced result of the joint workings of the Hebbian paradigm (nurture and cultural exposure) and harmonicity (auditory physics and biology).</strong>
DOI: 10.6084/m9.figshare.15261783
title: Final high resolution SUPERPOSE.zhanggroupRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261765
title: Final high resolution superpose.wishartlabRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261738
title: Final dynamutRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261726
title: DALIRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261726.v1
title: DALIRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.16378416
title: Data Analysis from: Altmetric Analysis of COVID-19 Research Published in 2020

description: The Dimensions and Altmetric.com databases are used as tools for the analysis of scientific production and the online attention received.
DOI: 10.6084/m9.figshare.15261804.v1
title: Final PANGO SUPERPOSE.zhanggroupRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261795.v1
title: Final PANGO superpose.wishartlabRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261783.v1
title: Final high resolution SUPERPOSE.zhanggroupRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261765.v1
title: Final high resolution superpose.wishartlabRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15261738.v1
title: Final dynamutRAW DATA

description: RAW DATA
DOI: 10.6084/m9.figshare.15173517.v1
title: RandomForest

description: Multi-fidelity tabular data for Random Forest hyperparameter space for HPOBench
DOI: 10.6084/m9.figshare.15155919.v1
title: XGBoost

description: Multi-fidelity tabular data for XGBoost hyperparameter space for HPOBench
DOI: 10.6084/m9.figshare.15156915.v1
title: NeuralNetwork

description: Multi-fidelity tabular data for Neural Network hyperparameter space for HPOBench
DOI: 10.6084/m9.figshare.15098283.v2
title: LogisticRegression

description: Multi-fidelity tabular data for Logistic Regression hyperparameter space for HPOBench
DOI: 10.17632/f2rd5vjpb5.1
title: Data for: Provenance of Late Jurassic-Early Cretaceous strata in the Mentelle Basin, southwestern Australia, reveals a trans-Gondwanan fluvial pathway

description: U–Pb monazite and zircon geochronology and zircon Hf isotopic data of sandstones from IODP Site U1515, Mentelle Basin
DOI: 10.17632/mchfk5dtks.2
title: Bibliography Data about Koronivia topics

description: Articles database of the Koronivia topics and SDGs for the bibliometrics and solutions meta-analyses
DOI: 10.6084/m9.figshare.15098280.v2
title: SupportVectorMachine

description: Multi-fidelity tabular data for Support Vector Machine hyperparameter space for HPOBench
DOI: 10.6084/m9.figshare.16380621
title: Institutionalisation_legislation_dataset.xlsx

description: Dataset for a study into the institutionalisation and evolution of the Polish Eurolect
DOI: 10.6084/m9.figshare.16380621.v1
title: Institutionalisation_legislation_dataset.xlsx

description: Dataset for a study into the institutionalisation and evolution of the Polish Eurolect
DOI: 10.26188/15177075.v1
title: cca r P. australensis table

description: cca table for r
DOI: 10.26188/15177114
title: cca r table P. lutea

description: cca table for r
DOI: 10.26188/15177114.v1
title: cca r table P. lutea

description: cca table for r
DOI: 10.26188/15177051
title: cca r metadata

description: metadata for r cca analysis
DOI: 10.26188/15177075
title: cca r P. australensis table

description: cca table for r
DOI: 10.26188/15177165
title: cca r taxonomy

description: taxonomy table for r cca
DOI: 10.26188/15177165.v1
title: cca r taxonomy

description: taxonomy table for r cca
DOI: 10.26188/15177051.v1
title: cca r metadata

description: metadata for r cca analysis
DOI: 10.26188/15176988
title: ASV table for alpha div microniches

description: 16S table for alpha diversity r microniches
DOI: 10.26188/15176988.v1
title: ASV table for alpha div microniches

description: 16S table for alpha diversity r microniches
DOI: 10.26188/15176910
title: 16S_r_ASV_table

description: ASV table 16S for r microniches analysis
DOI: 10.26188/15176940
title: 16S_taxonomy

description: 16S taxonomy for r microniches
DOI: 10.26188/15176940.v1
title: 16S_taxonomy

description: 16S taxonomy for r microniches
DOI: 10.26188/15176973.v1
title: 16S metadata r microniches

description: metadata table 16S r microniches
DOI: 10.26188/15176973
title: 16S metadata r microniches

description: metadata table 16S r microniches
DOI: 10.26188/15176910.v1
title: 16S_r_ASV_table

description: ASV table 16S for r microniches analysis
DOI: 10.26188/15176865
title: 18S_r_metadata

description: 18S metadata table
DOI: 10.26188/15176841
title: ASV_table_r_18S

description: Eukaryotic ASV table
DOI: 10.26188/15176841.v1
title: ASV_table_r_18S

description: Eukaryotic ASV table
DOI: 10.26188/15176853
title: 18S_r_taxonomy

description: 18S taxonomy file
DOI: 10.26188/15176853.v1
title: 18S_r_taxonomy

description: 18S taxonomy file
DOI: 10.26188/15176865.v1
title: 18S_r_metadata

description: 18S metadata table
DOI: 10.26188/15176772
title: O2_and_pH_gradients_table

description: table of o2 and pH gradients of each sample
DOI: 10.26188/15176766
title: Hyperspectral_data

description: hyperspectral reflectance data
DOI: 10.26188/15176772.v1
title: O2_and_pH_gradients_table

description: table of o2 and pH gradients of each sample
DOI: 10.26188/15065076
title: genVSske_consensus_tree.tre

description: tree for data analysis
DOI: 10.26188/15065076.v1
title: genVSske_consensus_tree.tre

description: tree for data analysis
DOI: 10.26188/15065052
title: ASV_10rem_rar_clr_tax_v2.tsv

description: table for data analysis
DOI: 10.26188/15065052.v1
title: ASV_10rem_rar_clr_tax_v2.tsv

description: table for data analysis
DOI: 10.26188/15065028.v1
title: taxonomy.tsv

description: table for data analysis
DOI: 10.26188/15065049
title: metadata_rar_10k.txt

description: table for data analysis
DOI: 10.26188/15065028
title: taxonomy.tsv

description: table for data analysis
DOI: 10.26188/15065049.v1
title: metadata_rar_10k.txt

description: table for data analysis
DOI: 10.26188/15065022
title: table_Ske+Phylo_tis.csv

description: table for data analysis
DOI: 10.26188/15065025
title: table_decontamined_genVSske.txt

description: table for data analysis
DOI: 10.26188/15065025.v1
title: table_decontamined_genVSske.txt

description: table for data analysis
DOI: 10.26188/15065022.v1
title: table_Ske+Phylo_tis.csv

description: table for data analysis
DOI: 10.26188/15064884
title: table_Ske+Phylo_ske.csv

description: table for data analysis
DOI: 10.26188/15063633
title: MicroCT skeletal properties

description: Skeletal properties analyzed by means of microCt scanning
DOI: 10.26188/15063270
title: Data % ASVs coral environment

description: % of ASVs shared between coral and environment
DOI: 10.26188/15063633.v1
title: MicroCT skeletal properties

description: Skeletal properties analyzed by means of microCt scanning
DOI: 10.26188/15064884.v1
title: table_Ske+Phylo_ske.csv

description: table for data analysis
DOI: 10.26188/15063228
title: cca_skeleton_ASV_to_tax

description: List of ASVs present in the cca skeleton biplot
DOI: 10.26188/15063234
title: cca_tissue_ASV_to_tax

description: List of ASVs present in the cca tissue biplot
DOI: 10.26188/15063234.v1
title: cca_tissue_ASV_to_tax

description: List of ASVs present in the cca tissue biplot
DOI: 10.26188/15063270.v2
title: Data % ASVs coral environment

description: % of ASVs shared between coral and environment
DOI: 10.26188/15063228.v1
title: cca_skeleton_ASV_to_tax

description: List of ASVs present in the cca skeleton biplot
DOI: 10.26188/15063264.v1
title: Supp Data 4 n2 fix sulf red

description: Bacterial functions
DOI: 10.26188/15063270.v1
title: Supp Data 5 % ASVs coral environment

description: % of ASVs shared between coral and environment
DOI: 10.26188/15063246.v2
title: Supp Data 1 LeFSe

description: Table reporting differently abundant ASVs of coral tissue and skeleton
DOI: 10.26188/15063261.v1
title: Supp Data 3 specie core microbiome

description: Coral Specie core microbiome
DOI: 10.26188/15063255.v1
title: Supp Data 2 core microbiome

description: scleractinian coral core microbiome
DOI: 10.26188/15063246
title: Supp. Table 1 - Data LeFSe

description: Table reporting differently abundant ASVs of coral tissue and skeleton
DOI: 10.26188/15063246.v4
title: Supp. Table 1 - Data LeFSe

description: Table reporting differently abundant ASVs of coral tissue and skeleton
DOI: 10.26188/15063246.v3
title: Data LeFSe

description: Table reporting differently abundant ASVs of coral tissue and skeleton
DOI: 10.26188/15063255
title: Supp. Table 2 - Data core microbiome

description: scleractinian coral core microbiome
DOI: 10.26188/15063255.v3
title: Supp. Table 2 - Data core microbiome

description: scleractinian coral core microbiome
DOI: 10.26188/15063255.v2
title: Data core microbiome

description: scleractinian coral core microbiome
DOI: 10.26188/15063261
title: Data species core microbiome

description: Coral Specie core microbiome
DOI: 10.26188/15063261.v3
title: Data species core microbiome

description: Coral Specie core microbiome
DOI: 10.26188/15063261.v2
title: Data specie core microbiome

description: Coral Specie core microbiome
DOI: 10.26188/15063264
title: Supp. Table 3 - Data n2 fix sulf red

description: Bacterial functions
DOI: 10.26188/15063264.v3
title: Supp. Table 3 - Data n2 fix sulf red

description: Bacterial functions
DOI: 10.26188/15063264.v2
title: Data n2 fix sulf red

description: Bacterial functions
DOI: 10.6084/m9.figshare.16381593.v1
title: Attitudinal analysis of polio vaccination: Level of vaccine skepticism and advocacy and their relationship with uncertainty and conspiracy mentality

description: Sample 1: Initial data of 310 individuals used for running EFA.Sample 2: Online data of 310 individuals for CFA<br>Combined Samples: Final data after combining samples of Phase 1 and Phase 2
DOI: 10.6084/m9.figshare.16381593
title: Attitudinal analysis of polio vaccination: Vaccine skepticism, advocacy and the influence of uncertainty and conspiracy mentality

description: Sample 1: Initial data of 310 individuals used for running EFA.Sample 2: Online data of 310 individuals for CFA<br>Combined Samples: Final data after combining samples of Phase 1 and Phase 2
DOI: 10.6084/m9.figshare.16381593.v3
title: Attitudinal analysis of polio vaccination: Vaccine skepticism, advocacy and the influence of uncertainty and conspiracy mentality

description: Sample 1: Initial data of 310 individuals used for running EFA.Sample 2: Online data of 310 individuals for CFA<br>Combined Samples: Final data after combining samples of Phase 1 and Phase 2
DOI: 10.6084/m9.figshare.16381593.v2
title: Attitudinal analysis of polio vaccination: Vaccine skepticism and advocacy and their relationship with uncertainty and conspiracy mentality

description: Sample 1: Initial data of 310 individuals used for running EFA.Sample 2: Online data of 310 individuals for CFA<br>Combined Samples: Final data after combining samples of Phase 1 and Phase 2
DOI: 10.5281/zenodo.4658971
title: Heterogeneity in transmissibility and shedding SARS-CoV-2 via droplets and aerosols

description: Raw data collected from the systematic review + outputs from analyses and models.
DOI: 10.5281/zenodo.4085219
title: Heterogeneity in transmissibility and shedding SARS-CoV-2 via droplets and aerosols

description: Raw data collected from the systematic review + outputs from analyses and models.
DOI: 10.5281/zenodo.5234326
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.16382274
title: Prevalence, distribution, and genotypes of adenovirus and norovirus in the Puzi River and its tributaries and the surrounding areas in Taiwan

description: AdVs prevalence is higher in the river than in other sites.<br>HAdV 41 and PAdV 5 are the dominant genotypes over all sample sites.Dominant NoVs genotypes are GII. 4 and GII. 17, they were associated with clinical cases
DOI: 10.6084/m9.figshare.16382274.v1
title: Prevalence, distribution, and genotypes of adenovirus and norovirus in the Puzi River and its tributaries and the surrounding areas in Taiwan

description: AdVs prevalence is higher in the river than in other sites.<br>HAdV 41 and PAdV 5 are the dominant genotypes over all sample sites.Dominant NoVs genotypes are GII. 4 and GII. 17, they were associated with clinical cases