cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25377/sussex.11637465
title: Dataset for paper "Anticipating causes and consequences" - Experiment 1 Early Effect Data with Differences

description: <b>Dataset for paper appearing in Journal of Memory and Language 2020</b><br>csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1200ms from the beginning of the conjunction "and so")<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.25377/sussex.11637465.v2
title: Dataset for paper "Anticipating causes and consequences" - Experiment 1 Early Effect Data with Differences

description: <b>Dataset for paper appearing in Journal of Memory and Language 2020</b><br>csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1200ms from the beginning of the conjunction "and so")<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.25377/sussex.11637465.v1
title: Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Early Effect Data with Differences

description: csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1200ms from the beginning of the conjunction "and so")<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.25377/sussex.11637447
title: Dataset for paper "Anticipating causes and consequences" Experiment 1 Very Early Effect Data with Differences

description: <b>Dataset for paper appearing in Journal of Memory and Language 2020</b><br>csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1500ms after beginning of the padding phrase in the first clause)<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.6084/m9.figshare.11637459
title: Brand-Evoked Mental Imagery: The Role of Brands Exerting Mental Imagery

description: Dataset provides evidence of the moderating role of brand familiarity and brand favorability in visual mental imagery. Also experimental input is provided
DOI: 10.6084/m9.figshare.11637459.v1
title: Brand-Evoked Mental Imagery: The Role of Brands Exerting Mental Imagery

description: Dataset provides evidence of the moderating role of brand familiarity and brand favorability in visual mental imagery. Also experimental input is provided
DOI: 10.6084/m9.figshare.11637327
title: Datasets and statistical analyses of 'No evidence of spontaneous preference for slowly moving objects in visually naïve chicks'

description: Datasets and statistical analyses of the following article 'No evidence of spontaneous preference for slowly moving objects in visually naïve chicks'<br>
DOI: 10.25377/sussex.11637447.v2
title: Dataset for paper "Anticipating causes and consequences" Experiment 1 Very Early Effect Data with Differences

description: <b>Dataset for paper appearing in Journal of Memory and Language 2020</b><br>csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1500ms after beginning of the padding phrase in the first clause)<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.6084/m9.figshare.11637264
title: Complete Gene results.BMC.sav

description: This is the data set of 11 SNPs and their association with PCOS in Sri Lankan women
DOI: 10.6084/m9.figshare.11637327.v1
title: Datasets and statistical analyses of 'No evidence of spontaneous preference for slowly moving objects in visually naïve chicks'

description: Datasets and statistical analyses of the following article 'No evidence of spontaneous preference for slowly moving objects in visually naïve chicks'<br>
DOI: 10.25377/sussex.11637447.v1
title: Dataset for paper "Anticipating causes and consequences" currently under review - Experiment 1 Very Early Effect Data with Differences

description: csv file for import into R as data frame<br>for the analysis:<br><br>Dependent Variable - dplooks - difference in proportion of looks to NP1 and NP2 pictures (averaged across 200 - 1500ms after beginning of the padding phrase in the first clause)<br>Independent Variable<br>VBias - causal bias of verb (note that consequentiality bias is to the other NP)<br><br>Sources of random effects<br>Part - participantsItem - items<br>IV is numerical, other variables are factors<br>Other variables are included in the file.
DOI: 10.6084/m9.figshare.11636940
title: Residual gravity anomaly over the area struck by 2016-2017 seismic events

description: The file contains the 250x250 m grid of the residual gravity anomaly over Central Italy between coordinates 826250-857250 E and 4728750-4759750 N (WGS84 UTM 32N). This dataset was created to perform 3D inversions of the gravity anomalies as described in the paper titled "3D gravity local inversion across the area struck by the 2016-2017 seismic events in Central Italy" by P. Mancinelli et al.
DOI: 10.6084/m9.figshare.11636940.v1
title: Residual gravity anomaly over the area struck by 2016-2017 seismic events

description: The file contains the 250x250 m grid of the residual gravity anomaly over Central Italy between coordinates 826250-857250 E and 4728750-4759750 N (WGS84 UTM 32N). This dataset was created to perform 3D inversions of the gravity anomalies as described in the paper titled "3D gravity local inversion across the area struck by the 2016-2017 seismic events in Central Italy" by P. Mancinelli et al.
DOI: 10.6084/m9.figshare.11636748
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>Additionally, we provide a Binder hosted interactive Jupyter notebook showing how to access the data via the Open Neurophysiology Environment (ONE) interface in Python : https://mybinder.org/v2/gh/int-brain-lab/paper-behavior-binder/master?filepath=one_example.ipynb<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com<br><i><b>Beta Disclaimer.</b> Please note that this is a beta version of the IBL dataset, which is still undergoing final quality checks. If you find any issues or inconsistencies in the data, please contact us at info+behavior@internationalbrainlab.org .</i><br>
DOI: 10.6084/m9.figshare.11636748.v1
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.6084/m9.figshare.11636748.v2
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.6084/m9.figshare.11636748.v3
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.6084/m9.figshare.11636748.v4
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>Additionally, we provide a Binder hosted interactive Jupyter notebook showing how to access the data via the Open Neurophysiology Environment (ONE) interface in Python : https://mybinder.org/v2/gh/int-brain-lab/paper-behavior-binder/master?filepath=one_example.ipynb<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.6084/m9.figshare.11636748.v5
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>Additionally, we provide a Binder hosted interactive Jupyter notebook showing how to access the data via the Open Neurophysiology Environment (ONE) interface in Python : https://mybinder.org/v2/gh/int-brain-lab/paper-behavior-binder/master?filepath=one_example.ipynb<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.6084/m9.figshare.11636748.v6
title: A standardized and reproducible method to measure decision-making in mice: Data

description: Behavioral data associated with the IBL paper: <i>A standardized and reproducible method to measure decision-making in mice.</i><i><br></i>This data set contains contains 3 million choices 101 mice across seven laboratories at six different research institutions in three countries obtained during a perceptual decision making task.<i><br></i>When citing this data, please also cite the associated paper: https://doi.org/10.1101/2020.01.17.909838<br>This data can also be accessed using DataJoint and web browser tools at data.internationalbrainlab.org<br>Additionally, we provide a Binder hosted interactive Jupyter notebook showing how to access the data via the Open Neurophysiology Environment (ONE) interface in Python : https://mybinder.org/v2/gh/int-brain-lab/paper-behavior-binder/master?filepath=one_example.ipynb<br>For more information about the International Brain Laboratory please see our website: www.internationalbrainlab.com
DOI: 10.25392/leicester.data.11636679.v1
title: Effects of Word Predictability on Eye Movements during Arabic Reading

description: The folder contains data files and R analysis code for two eye movement experiments that investigated word predictability effects in Arabic. Stimuli were two sets of 72 sentence frames that included one of two interchangeable target words. These had either high or low predictability from the prior sentence context. Experiment 1 used a variety of long 4- to 8-letter words of varying morphological complexity and Experiment 2 used short 3- to 4-letter nouns as target words. Separate excel spreadsheets of data are included for Experiments 1 and 2, along with the R analysis script that was used for both experiments.
DOI: 10.6084/m9.figshare.11636595
title: KLEE herbivore dung data

description: The data file contains the biomass of dung piles and the carbon, nitrogen and phosphorus concentration of herbivore dung collected in the study. The data file consists of 3 sheets. Sheet 1 is the metadata explaining the column headings in sheet 2. Sheet 2 contains the biomass of dung piles collected per herbivore species. Sheet 3 contains the dung nutrient data of the herbivore species.
DOI: 10.6084/m9.figshare.11636595.v1
title: KLEE herbivore dung data

description: The data file contains the biomass of dung piles and the carbon, nitrogen and phosphorus concentration of herbivore dung collected in the study. The data file consists of 3 sheets. Sheet 1 is the metadata explaining the column headings in sheet 2. Sheet 2 contains the biomass of dung piles collected per herbivore species. Sheet 3 contains the dung nutrient data of the herbivore species.
DOI: 10.6084/m9.figshare.11636577
title: KLEE grass and tree data

description: The data file contains the carbon, nitrogen and phosphorus concentrations of bulk grass samples and <i>Acacia drepanolobium</i> leaves collected in the study. The data file consists of 3 sheets. Sheet 1 is the metadata explaining the column headings in sheets 2 and 3. Sheet 2 contains the nutrient concentrations of clipped grass samples in the KLEE plots. Sheet 3 contains the nutrient concentrations of collected tree leaves in the KLEE plots. Sheet 3 also contains the tree density and canopy cover estimates of each KLEE plot.<br><br>
DOI: 10.6084/m9.figshare.11636577.v2
title: KLEE grass and tree data

description: The data file contains the carbon, nitrogen and phosphorus concentrations of bulk grass samples and <i>Acacia drepanolobium</i> leaves collected in the study. The data file consists of 3 sheets. Sheet 1 is the metadata explaining the column headings in sheets 2 and 3. Sheet 2 contains the nutrient concentrations of clipped grass samples in the KLEE plots. Sheet 3 contains the nutrient concentrations of collected tree leaves in the KLEE plots. Sheet 3 also contains the tree density and canopy cover estimates of each KLEE plot.<br><br>
DOI: 10.6084/m9.figshare.11636502
title: KLEE soil data

description: The data file contains the soil data collected in the study. The data file consists of 2 sheets. Sheet 1 is the metadata explaining the column headings in sheet 2. Sheet 2 contains the soil carbon and nutrient measurements in plots of the KLEE experiment.
DOI: 10.6084/m9.figshare.11636577.v1
title: KLEE grass and tree data

description: The data file contains the carbon, nitrogen and phosphorus concentrations of bulk grass samples and <i>Acacia drepanolobium</i> leaves collected in the study. The data file consists of 3 sheets. Sheet 1 is the metadata explaining the column headings in sheets 2 and 3. Sheet 2 contains the nutrient concentrations of clipped grass samples in the KLEE plots. Sheet 3 contains the nutrient concentrations of collected tree leaves in the KLEE plots.<br><br>
DOI: 10.6084/m9.figshare.11636499
title: How context influences functionality of community-level health governance structures: a case study of community health committees in Kenya

description: This is a dataset contains transcripts of FGDs and interviews on how contextual factors influence the functionality of community health committees.
DOI: 10.6084/m9.figshare.11636430
title: MOESM3 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 3: Table S3. Summary of 52 randomised trials stopped early for futility: results
DOI: 10.6084/m9.figshare.11636430.v1
title: MOESM3 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 3: Table S3. Summary of 52 randomised trials stopped early for futility: results
DOI: 10.6084/m9.figshare.11636421
title: MOESM2 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 2: Table S2. Summary of 52 randomised trials stopped early for futility: selected statistical features
DOI: 10.6084/m9.figshare.11636421.v1
title: MOESM2 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 2: Table S2. Summary of 52 randomised trials stopped early for futility: selected statistical features
DOI: 10.6084/m9.figshare.11636415
title: MOESM1 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 1: Table S1. Summary of 52 randomised trials stopped early for futility: authors, subject, and futility analysis
DOI: 10.6084/m9.figshare.11636415.v1
title: MOESM1 of A systematic survey of randomised trials that stopped early for reasons of futility

description: Additional file 1: Table S1. Summary of 52 randomised trials stopped early for futility: authors, subject, and futility analysis
DOI: 10.6084/m9.figshare.11636394
title: Additional file 8 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 8. Table S4. Comparisons of marker loci detected in this study with loci reported previously.
DOI: 10.6084/m9.figshare.11636394.v2
title: Additional file 8 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 8. Table S4. Comparisons of marker loci detected in this study with loci reported previously.
DOI: 10.6084/m9.figshare.11636394.v1
title: MOESM8 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 8. Table S4. Comparisons of marker loci detected in this study with loci reported previously.
DOI: 10.6084/m9.figshare.11636388
title: Additional file 7 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 7. Table S3. Analysis of molecular variance (AMOVA) for six subpopulations of rice accessions.
DOI: 10.6084/m9.figshare.11636388.v2
title: Additional file 7 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 7. Table S3. Analysis of molecular variance (AMOVA) for six subpopulations of rice accessions.
DOI: 10.6084/m9.figshare.11636388.v1
title: MOESM7 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 7. Table S3. Analysis of molecular variance (AMOVA) for six subpopulations of rice accessions.
DOI: 10.6084/m9.figshare.11636379
title: Additional file 6 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 6. Table S2. The code, name and origin of 542 rice accessions and the Q value of each accession belonging to the 6 subpopulations in this study.
DOI: 10.6084/m9.figshare.11636379.v1
title: MOESM6 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 6. Table S2. The code, name and origin of 542 rice accessions and the Q value of each accession belonging to the 6 subpopulations in this study.
DOI: 10.6084/m9.figshare.11636379.v2
title: Additional file 6 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 6. Table S2. The code, name and origin of 542 rice accessions and the Q value of each accession belonging to the 6 subpopulations in this study.
DOI: 10.6084/m9.figshare.11636376
title: Additional file 5 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 5. Table S1. Summary statistics for the 266 SSR markers used in this study.
DOI: 10.6084/m9.figshare.11636376.v1
title: MOESM5 of Mining of favorable alleles for seed reserve utilization efficiency in Oryza sativa by means of association mapping

description: Additional file 5. Table S1. Summary statistics for the 266 SSR markers used in this study.
DOI: 10.6084/m9.figshare.11636331
title: Additional file 1: of Research on retention forestry in Northern Europe

description: Supplementary material. 3 Appendix A literature on retention (Excel file with 4 worksheets).
DOI: 10.6084/m9.figshare.11636331.v1
title: Additional file 1: of Research on retention forestry in Northern Europe

description: Supplementary material. 3 Appendix A literature on retention (Excel file with 4 worksheets).
DOI: 10.6084/m9.figshare.11636301
title: MOESM1 of A method for functional testing constitutive and ligand-induced interactions of lysin motif receptor proteins

description: Additional file 1: Table S1. List of primers used in this study. Table S2. List of plasmids used in this study. Table S3. Transformation efficiency of L. japonicus MG-20 as estimated by the ratio of GUS-positive hairy roots to the total number of formed hairy roots. Table S4. Transformation efficiency of the L. japonicus mutants nfr1-1 and nfr5-2 as estimated by the ratio of GUS-positive hairy roots to the total number of formed hairy roots.