cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23309159.v1
title: Occupancy data

description: Dataset used to run the occupancy models described in <em>Lydia K.D. Katsis, Tessa A. Rhinehart, Elizabeth Dorgay, Emma E. Sanchez, C. Patrick Doncaster, Jake L. Snaddon, Justin Kitzes. A comparison of statistical methods for deriving occupancy estimates from acoustic monitoring data.</em>
<br>
Data consists of
<strong>Ground-truth</strong>
1) ground_truth_data.csv: csv of manually reviewed files for presence or absence of howler monkeys, used as benchmark to compare modelled occupany estimates.
<br>
<strong>Partially annotated datasets</strong>
1) top_ten_annotated.csv : files with top-10 machine learning scores per site manually reviewed
2) random_ten_annotated.csv : 10 randomly selected files per site manually reviewed
3) scheduled_listening_annotated.csv: first file after 5am every 3 days from each site manually reviewed.
<br>
<strong>Machine learning predictions on</strong> <strong>temporally subset dataset</strong>
1) dawn_all.csv : full dataset of predictions, with no subsetting
2) dawn_10_max.csv : temporal interval of 10 minutes, with file with maximum machine learning score sampled
3) dawn_10_random.csv: temporal interval of 10 minutes, first file sampled
4) dawn_30_max.csv: temporal interval of 30 minutes, with file with maximum machine learning score sampled
5) dawn_30_random.csv: temporal interval of 30 minutes, first file sampled
<br>
<br>
Columns in data consist of:

 LocationID/site: unique identifier for recorder location
 date/timestamp: when the recording was made
 annotation: manualy review for presence (1) or absence (0) of howler monkey in clip
 logit_present: machine learning score with logit transformation 
 softmax_present: machine learning score with softmax transformation 

<br>
DOI: 10.5517/ccdc.csd.cc2g0jlm
title: CCDC 2264630: Experimental Crystal Structure Determination

description: Related Article: Rebecca Birolo, Federica Bravetti, Eugenio Alladio, Emanuele Priola, Gianluca Bianchini, Rubina Novelli, Andrea Aramini, Roberto Gobetto, Michele R. Chierotti|2023|Cryst.Growth Des.|23|7898|doi:10.1021/acs.cgd.3c00696
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.cc2g0jnp
title: CCDC 2264632: Experimental Crystal Structure Determination

description: Related Article: Rebecca Birolo, Federica Bravetti, Eugenio Alladio, Emanuele Priola, Gianluca Bianchini, Rubina Novelli, Andrea Aramini, Roberto Gobetto, Michele R. Chierotti|2023|Cryst.Growth Des.|23|7898|doi:10.1021/acs.cgd.3c00696
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.cc2g0jpq
title: CCDC 2264633: Experimental Crystal Structure Determination

description: Related Article: Rebecca Birolo, Federica Bravetti, Eugenio Alladio, Emanuele Priola, Gianluca Bianchini, Rubina Novelli, Andrea Aramini, Roberto Gobetto, Michele R. Chierotti|2023|Cryst.Growth Des.|23|7898|doi:10.1021/acs.cgd.3c00696
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.cc2g0jqr
title: CCDC 2264634: Experimental Crystal Structure Determination

description: Related Article: Rebecca Birolo, Federica Bravetti, Eugenio Alladio, Emanuele Priola, Gianluca Bianchini, Rubina Novelli, Andrea Aramini, Roberto Gobetto, Michele R. Chierotti|2023|Cryst.Growth Des.|23|7898|doi:10.1021/acs.cgd.3c00696
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: 10.15468/dl.3x7yz2
title: Occurrence Download

description: A dataset containing 2327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is South America",
 "OccurrenceStatus is Present",
 "TaxonKey is Ateles paniscus (Linnaeus, 1758)"
 ]
}

 The dataset includes 2327 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025126-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sq4q9b
title: Occurrence Download

description: A dataset containing 11423 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "DatasetKey is EOD – eBird Observation Dataset",
 "TaxonKey is Gypaetus barbatus (Linnaeus, 1758)"
 ]
}

 The dataset includes 11423 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025127-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mravmc
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia peninsularis (Britton & Rose) Standl.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 52 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025128-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jtw8tw
title: Occurrence Download

description: A dataset containing 7335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Human Observation, Living Specimen, Fossil)",
 "Continent is Asia",
 "TaxonKey is Camellia L."
 ]
}

 The dataset includes 7335 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025125-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/q2eu-p2rv
title: Measurement of Inorganics in precipitation at Els Torms

description: Measurement of Inorganics in precipitation at Els Torms
DOI: 10.48597/9yqm-27a8
title: Measurement of Inorganics in precipitation at Els Torms

description: Measurement of Inorganics in precipitation at Els Torms
DOI: 10.48597/kt2x-x7nm
title: Inorganics in precipitation at Els Torms

description: Measurement of Inorganics in precipitation at Els Torms
DOI: 10.48597/myc9-sss5
title: Measurement of Inorganics in precipitation at Els Torms

description: Measurement of Inorganics in precipitation at Els Torms
DOI: 10.48597/qk56-tm5f
title: Measurement of Inorganics in precipitation at Els Torms

description: Measurement of Inorganics in precipitation at Els Torms
DOI: 10.15468/dl.cwsn8d
title: Occurrence Download

description: A dataset listing the 123 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((31.94233 37.16362,34.72154 37.16362,34.72154 38.45973,31.94233 38.45973,31.94233 37.16362))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 2017-2017"
 ]
}

 The dataset's 123 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025117-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tharv5
title: Occurrence Download

description: A dataset containing 9408 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ITA",
 "OccurrenceStatus is Present",
 "TaxonKey is Psittacula krameri (Scopoli, 1769)"
 ]
}

 The dataset includes 9408 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025130-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34973/hs7d-k757
title: Sensorimotor trade-off in Parkinson

description: This dataset contains behavioural data from a virtual ball catching task in Parkinson patients and age matched controls. Methods and results are described in PhD-thesis of Sonal Sengupta.
DOI: 10.15468/dl.juz8vt
title: Occurrence Download

description: A dataset containing 1902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia pennatula (Schltdl. & Cham.) Benth.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1902 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025131-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28652075
title: Behavioral scores.xlsx

description: Behavioral data (Rating scores to videos from questionnaire) to public speakings
DOI: 10.15468/dl.j8b8ek
title: Occurrence Download

description: A dataset containing 461 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Material sample, Specimen)",
 "TaxonKey is Eumops perotis (Schinz, 1821)",
 "Year 1970-2025"
 ]
}

 The dataset includes 461 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025133-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nyugzq
title: Occurrence Download

description: A dataset containing 937 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia polyphylla Clos, Acacia polyphylla DC.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 937 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025134-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sedbhc
title: Occurrence Download

description: A dataset listing the 10 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Living Specimen, Occurrence evidence)",
 "Geometry POLYGON((4.69248 43.28837,4.96096 43.28837,4.96096 43.47507,4.69248 43.47507,4.69248 43.28837))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chiroptera",
 "Year 2020-2025"
 ]
}

 The dataset's 10 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025124-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7266/n7-4y30-bv62
title: CTD, ADCP, meteorological, and flow-through instrumental data collected onboard the R/V Weatherbird II cruise WB0517 in the northwestern margin of Cuba from 2017-05-09 to 2017-05-25
DOI: 10.5281/zenodo.15019866
title: Enhancing Lettuce Classification: Optimizing Spectral Wavelength Selection via CCARS and PLS-DA

description: This dataset has been utilized in a manuscript titled Evaluating and Optimizing Wavelength Selection Using the CCARS Algorithm and Spectroscopy Signals for Lettuce Classification Leveraging PLS-DA Model. The study leverages this detailed spectral data to evaluate and optimize wavelength selection and to classify lettuce health using advanced analytical models, such as PLS-DA, supported by the CCARS algorithm for enhanced signal processing and feature selection.

It comprises spectral measurements collected from lettuce plant leaves, with each row representing a distinct reflectance reading taken during a specific acquisition session. The structure is organized with the following key attributes:

Date & Day. The Date column indicates the exact day of measurement, while the Day column may represent a sequential experimental day or a relative timeline indicator. These two columns are highly correlated.

 Acquisition. This column records the acquisition number, signifying the instance of measurement sessions performed on a given day. It helps differentiate multiple sessions that might occur within the same day.

Position. Each plant is assigned a unique identifier in the Position column, ensuring that measurements can be traced back to individual subjects. This is essential for analyzing variability across different plants.

N. The N column indicates the number of samples recorded during a single acquisition on the same plant, providing insight into the sample size and measurement frequency.

Wavelength. Spectral data is recorded at various wavelengths, and this column specifies the wavelength at which each reflectance measurement was captured, expressed in nanometers (nm).

Reflectance. This column holds the actual measured reflectance values, which are the core data points used to analyze the spectral characteristics of the lettuce leaves, expressed as absolute values.

Class. The binary Class column categorizes the plant's health status, as Healthy or Unhealthy, enabling further analysis or predictive modeling based on spectral data.
DOI: 10.5281/zenodo.15019865
title: Enhancing Lettuce Classification: Optimizing Spectral Wavelength Selection via CCARS and PLS-DA

description: This dataset has been utilized in a manuscript titled Evaluating and Optimizing Wavelength Selection Using the CCARS Algorithm and Spectroscopy Signals for Lettuce Classification Leveraging PLS-DA Model. The study leverages this detailed spectral data to evaluate and optimize wavelength selection and to classify lettuce health using advanced analytical models, such as PLS-DA, supported by the CCARS algorithm for enhanced signal processing and feature selection.

It comprises spectral measurements collected from lettuce plant leaves, with each row representing a distinct reflectance reading taken during a specific acquisition session. The structure is organized with the following key attributes:

Date & Day. The Date column indicates the exact day of measurement, while the Day column may represent a sequential experimental day or a relative timeline indicator. These two columns are highly correlated.

 Acquisition. This column records the acquisition number, signifying the instance of measurement sessions performed on a given day. It helps differentiate multiple sessions that might occur within the same day.

Position. Each plant is assigned a unique identifier in the Position column, ensuring that measurements can be traced back to individual subjects. This is essential for analyzing variability across different plants.

N. The N column indicates the number of samples recorded during a single acquisition on the same plant, providing insight into the sample size and measurement frequency.

Wavelength. Spectral data is recorded at various wavelengths, and this column specifies the wavelength at which each reflectance measurement was captured, expressed in nanometers (nm).

Reflectance. This column holds the actual measured reflectance values, which are the core data points used to analyze the spectral characteristics of the lettuce leaves, expressed as absolute values.

Class. The binary Class column categorizes the plant's health status, as Healthy or Unhealthy, enabling further analysis or predictive modeling based on spectral data.
DOI: 10.5281/zenodo.15077441
title: Permafrost thaw reverses soil carbon age profiles and extends transit time in an Arctic tundra soil

description: Files for the manuscript “Permafrost thaw reverses soil carbon age profiles and extends transit time in an Arctic tundra soil”.

 
description: A vertically-resolved model was developed and optimized against radiocarbon (14C) data from a 25-year snow manipulation experiment to quantify how deeper snow affects soil carbon age, transit time, and redistribution in Arctic permafrost.
DOI: 10.15468/dl.995fdv
title: Occurrence Download

description: A dataset containing 246 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acacia pringlei Rose)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 246 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025136-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8362803
title: Robust detection of SARS-CoV-2 exposure in population using T-cell repertoire profiling

description: The dataset contains processed T-cell receptor repertoire sequencing data from >1200 individuals of different sex and age. Note that only samples with good sequencing coverage are published (>10^5 reads per file). 
The main aim of our study is to find TCR sequence biomarkers and develop a bioinformatic pipeline that allows building an accurate and robust classifier that distinguishes COVID-19-convalescent donors from unexposed individuals. We performed immunosequencing of the rearranged TCR α and β regions for PBMCs. For the cohort described in this study (Cohort-I) we sequence both chains of the TCR heterodimer as both of these chains are required to properly predict antigen recognition26. We ran conventional T-cell repertoire data analysis and pre-processed data to remove low-coverage samples. 
Of samples in Cohort-I which passed read count threshold, 383/377 TCR α/β samples were from healthy donors (SARS-CoV-2 PCR test negative or obtained prior to pandemic) and 890/848 were from COVID-19-positive patients. The majority of samples were accompanied by information on HLA class I and II alleles. Samples were prepared and sequenced in nine batches.
We proceed with selecting a set of CDR3 sequences that can serve as biomarkers and form a feature list for COVID-19 status classifier. We also validate the resulting set of clonotypes in several ways. Co-occurence of specific TCR α and β clonotypes can serve as an independent validation for biomarkers and their co-association with some specific pathogen. Additional information on donor HLAs is provided to filter the set of biomarkers based on HLA restriction: association with donor HLA serves as an additional evidence for TCR specificity to a specific set of antigens presented in a given donor and allows detecting the fingerprint of past and present infection. Furthermore, clonotypes with similar sequences can be aggregated into 'metaclonotype' biomarkers based on clonotype graph analysis.
Finally, we train various COVID-19 status classifiers on selected batches from Cohort-I data using different algorithms and incorporating different feature sets. Verification of the robustness of our results was performed using independent batches of the Cohort-I and data from Cohort-II published previously.
DOI: 10.17632/v7ppsjgz46.1
title: Processing tomato - Genotype x Environment
DOI: 10.17632/v7ppsjgz46.2
title: Processing tomato - Genotype x Environment
DOI: 10.15468/dl.8kw2xa
title: Occurrence Download

description: A dataset containing 1730 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Corythornis madagascariensis (Linnaeus, 1766)"
 ]
}

 The dataset includes 1730 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025137-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/yk6zz8mphb.1
title: 2025_Cutts_et_al_QTrap_analysis

description: Contains a script and two files to demonstrate Qtrap analysis where bead position is used to estimate the length of braided DNA and angle between them during a force distance curve. This assumes that the length of the two DNAs remains the same length. 

Analysis used in: Cutts et al, 2024, "Substrate accessibility regulation of human TopIIa decatenation by cohesin".
Preprint available at: https://www.biorxiv.org/content/10.1101/2023.11.20.567865v1
DOI: 10.5281/zenodo.15077546
title: Your nose knows what you're looking for!

description: DATA DESCRIPTION

 

Detection Task

The Excel file titled “DetectionTaskResults.xlsx” contains average detection and washing-out times (in seconds) for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).

 

Visual Search Task

The Excel file titled “VisualSearchTaskResults.xlsx” contains discrimination performances and average discrimination times for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).

This Excel file also includes a table with all the data necessary for error analysis. The table reports:

·      The participant code (from S01 to S22)

·      The trial number where the participant made an error

·      The congruency condition of that trial (NaN = no-odorant, 1 = congruent, 2 = target-incongruent, 3 = distractor-congruent)

·      The odorant delivered (NaN = Neutral, 1 = Strawberry, 2 = Apple, 3 = Lemon)

·      The visual target shown (1 = Strawberry, 2 = Yellow Apple, 3 = Green Apple, 4 = Red Apple, 5 = Lemon)

·      The distractor selected (i.e., the name of a fruit in Italian)

·      The error code (0 = Color & Odorant match; 1 = Color match - Odor mismatch; 2 = Odor match - Color mismatch; 3 = Color & Odorant mismatch)

 

Discrimination Task

The Excel file titled “DiscriminationTaskResults.xlsx” contains discrimination performances and average discrimination times for each participant (coded from S01 to S22) and each target fruit (strawberry, apple, and lemon).