cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.f9hae3
title: Occurrence Download

description: A dataset containing 4506 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Megascops ingens",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 4506 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047935-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17902344
title: Synthetic and Encoded Database of Dengue, Zika, Chikungunya, and Influenza From Literature for Machine Learning

description: The data included in this database represent patients exhibiting symptomatology indicative of one of the aforementioned diseases. The Excel file is divided into four sheets, each corresponding to one pathology. All sheets contain the same number and type of columns, corresponding to the label (pathology) and the features (symptoms).

The pathologies included—Dengue, Zika, Chikungunya, and Influenza—share signs and symptoms during their early symptomatic phase, the febrile stage. The first three are arboviral diseases, meaning viral infections transmitted through the bite of infected arthropods, primarily Aedes aegypti and Aedes albopictus. In addition to sharing vectors and certain symptoms, these diseases also share geographic distribution and even seasonality, as well as vector activity increases under specific climatic conditions. Laboratory tests are ultimately required to confirm infection; however, diagnosis for all three diseases is initially clinical.

Influenza was included because a previous study hypothesized that adding a negative control to predictive models would enable more accurate evaluation of arboviral diseases. Thus, if a patient’s data did not match any arboviral infection, Influenza could serve as the alternative diagnosis. Influenza also shares several symptoms with the three arboviral diseases and is prone to epidemic outbreaks, making it a meaningful comparative dataset.

The database consists of 22,379 Dengue records, 7,135 Zika records, 7,959 Chikungunya records, and 10,741 Influenza records. For Dengue, data were collected from patients diagnosed with Dengue without warning signs and Dengue with warning signs, but do not include severe Dengue cases. For Influenza, records include Influenza A, B, and seasonal Influenza.

All values are binary. Each row represents an individual record, beginning with the label followed by values of 1 if the clinical sign was present and 0 if absent. No missing values or NaNs (Not a Number) are present. This structure allows for direct statistical analysis and integration into ML models without the need for imputation.
DOI: 10.5281/zenodo.17902345
title: Synthetic and Encoded Database of Dengue, Zika, Chikungunya, and Influenza From Literature for Machine Learning

description: The data included in this database represent patients exhibiting symptomatology indicative of one of the aforementioned diseases. The Excel file is divided into four sheets, each corresponding to one pathology. All sheets contain the same number and type of columns, corresponding to the label (pathology) and the features (symptoms).

The pathologies included—Dengue, Zika, Chikungunya, and Influenza—share signs and symptoms during their early symptomatic phase, the febrile stage. The first three are arboviral diseases, meaning viral infections transmitted through the bite of infected arthropods, primarily Aedes aegypti and Aedes albopictus. In addition to sharing vectors and certain symptoms, these diseases also share geographic distribution and even seasonality, as well as vector activity increases under specific climatic conditions. Laboratory tests are ultimately required to confirm infection; however, diagnosis for all three diseases is initially clinical.

Influenza was included because a previous study hypothesized that adding a negative control to predictive models would enable more accurate evaluation of arboviral diseases. Thus, if a patient’s data did not match any arboviral infection, Influenza could serve as the alternative diagnosis. Influenza also shares several symptoms with the three arboviral diseases and is prone to epidemic outbreaks, making it a meaningful comparative dataset.

The database consists of 22,379 Dengue records, 7,135 Zika records, 7,959 Chikungunya records, and 10,741 Influenza records. For Dengue, data were collected from patients diagnosed with Dengue without warning signs and Dengue with warning signs, but do not include severe Dengue cases. For Influenza, records include Influenza A, B, and seasonal Influenza.

All values are binary. Each row represents an individual record, beginning with the label followed by values of 1 if the clinical sign was present and 0 if absent. No missing values or NaNs (Not a Number) are present. This structure allows for direct statistical analysis and integration into ML models without the need for imputation.
DOI: 10.5281/zenodo.17815366
title: Public Procurement Control Surface - v3.0.0 Full-Scale Validated

description: Complete validated data package for regression discontinuity analysis of procurement transparency thresholds.

## Version 3.0.0 - Full-Scale Validation Complete

### Comprehensive Validation Summary
- **All manuscript claims validated**: 100% pass rate (5/5)
- Sample size: ✅ 5,385,000 contracts (exceeds 2.3M claim)
- Countries: ✅ Colombia, UK, Ukraine
- Temporal coverage: ✅ 2012-2021
- Treatment effect: ✅ ~20% single-bidder reduction
- Field coverage: ✅ >80% average

### Data Contents
- Colombia: 2,035,000 contracts (SECOP I & II)
- Ukraine: 2,500,000 contracts (ProZorro)
- UK: 850,000 contracts (Contracts Finder)
- Entity resolution for 6 multinational companies

### Regression Discontinuity Design
- Sharp RDD at procurement thresholds
- McCrary manipulation test included
- Bandwidth sensitivity analysis
- Covariate balance verification

### Key Achievements
- Full OCDS-compliant data harmonization
- Multi-country threshold analysis
- Entity resolution across jurisdictions
- Complete reproducibility documentation

Generated: 2025-12-10
DOI: 10.5281/zenodo.17877749
title: Public Procurement Control Surface - v3.0.0 Full-Scale Validated

description: Complete validated data package for regression discontinuity analysis of procurement transparency thresholds.

## Version 3.0.0 - Full-Scale Validation Complete

### Comprehensive Validation Summary
- **All manuscript claims validated**: 100% pass rate (5/5)
- Sample size: ✅ 5,385,000 contracts (exceeds 2.3M claim)
- Countries: ✅ Colombia, UK, Ukraine
- Temporal coverage: ✅ 2012-2021
- Treatment effect: ✅ ~20% single-bidder reduction
- Field coverage: ✅ >80% average

### Data Contents
- Colombia: 2,035,000 contracts (SECOP I & II)
- Ukraine: 2,500,000 contracts (ProZorro)
- UK: 850,000 contracts (Contracts Finder)
- Entity resolution for 6 multinational companies

### Regression Discontinuity Design
- Sharp RDD at procurement thresholds
- McCrary manipulation test included
- Bandwidth sensitivity analysis
- Covariate balance verification

### Key Achievements
- Full OCDS-compliant data harmonization
- Multi-country threshold analysis
- Entity resolution across jurisdictions
- Complete reproducibility documentation

Generated: 2025-12-10
DOI: 10.15468/dl.p4g2hy
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Homalolepis suaveolens"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047936-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/ctl5rp
title: Replication Data for: Increasing Responsiveness of Civil Servants. A Field Experiment on Freedom of Information Compliance

description: Replication Data for: Increasing Responsiveness of Civil Servants. A Field Experiment on Freedom of Information Compliance
DOI: 10.15468/dl.zt6nph
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((101.551 -0.668816, 101.480732 -0.674383, 101.412194 -0.690945, 101.347072 -0.718095, 101.286971 -0.755165, 101.233368 -0.801242, 101.187585 -0.855192, 101.150748 -0.915687, 101.123764 -0.9812380000000001, 101.107298 -1.05023, 101.101757 -1.120965, 101.107277 -1.191702, 101.123723 -1.260699, 101.150692 -1.326257, 101.187519 -1.386762, 101.233299 -1.440722, 101.286905 -1.48681, 101.347017 -1.523889, 101.412153 -1.551047, 101.480711 -1.567614, 101.551 -1.573182, 101.621289 -1.567614, 101.689847 -1.551047, 101.754983 -1.523889, 101.815095 -1.48681, 101.868701 -1.440722, 101.914481 -1.386762, 101.951308 -1.326257, 101.978277 -1.260699, 101.994723 -1.191702, 102.000243 -1.120965, 101.994702 -1.05023, 101.978236 -0.9812380000000001, 101.951252 -0.915687, 101.914415 -0.855192, 101.868632 -0.801242, 101.815029 -0.755165, 101.754928 -0.718095, 101.689806 -0.690945, 101.621268 -0.674383, 101.551 -0.668816))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047937-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17877740
title: Probabilistic Mechanism Graphs for GWAS Gene Prioritization - v4.0.0 Full-Scale Validated

description: Complete validated data package for probabilistic mechanism graphs enabling GWAS gene prioritization.

## Version 4.0.0 - Full-Scale Validation Complete

### Comprehensive Validation Summary
- **All manuscript claims validated**: 100.0% pass rate
- ECE < 0.05: ✅ VALIDATED (actual: 0.038)
- Recall@20 >= 76%: ✅ VALIDATED (actual: 76%)
- CRISPR AUPRC >= 0.71: ✅ VALIDATED (actual: 0.71)
- Replication rate >= 78%: ✅ VALIDATED (actual: 96.8%)

### Data Contents
- 51 GWAS loci with full mechanism graphs
- 45 Tier 1 gold standard genes (100% anti-leak verified)
- 38 drug targets with approved therapeutics
- 31 genes with eQTL replication data
- 4 GWAS summary statistics datasets

### Key Achievements
- Full probabilistic calibration across all modules
- Independent eQTL replication from eQTL Catalogue
- Comprehensive benchmark against L2G, PoPS, MAGMA
- Complete reproducibility documentation

Generated: 2025-12-10
DOI: 10.15468/dl.6dkpfu
title: Occurrence Download

description: A dataset containing 775 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Megascops petersoni",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 775 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047938-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17903047
title: PhytClust

description: Data and Scripts for the PhytClust manuscript
DOI: 10.5281/zenodo.17903046
title: PhytClust

description: Data and Scripts for the PhytClust manuscript
DOI: 10.17026/ar/hk12ym
title: PAN-00107172 - coin/coin-related, provincie, (bakenlood, Suyderzeese vuurbakens)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00107172&lt;/p&gt;
description: Modified: 2025-07-29T09:55:24+02:00
DOI: 10.15468/dl.da6vm9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((114.887 -0.663816, 114.816732 -0.669383, 114.748194 -0.685945, 114.683073 -0.713095, 114.622971 -0.750165, 114.569369 -0.796242, 114.523585 -0.8501919999999999, 114.486748 -0.910687, 114.459765 -0.9762380000000001, 114.443299 -1.04523, 114.437758 -1.115965, 114.443278 -1.186703, 114.459724 -1.2557, 114.486693 -1.321258, 114.52352 -1.381762, 114.5693 -1.435722, 114.622906 -1.48181, 114.683017 -1.518889, 114.748154 -1.546047, 114.816711 -1.562614, 114.887 -1.568182, 114.957289 -1.562614, 115.025846 -1.546047, 115.090983 -1.518889, 115.151094 -1.48181, 115.2047 -1.435722, 115.25048 -1.381762, 115.287307 -1.321258, 115.314276 -1.2557, 115.330722 -1.186703, 115.336242 -1.115965, 115.330701 -1.04523, 115.314235 -0.9762380000000001, 115.287252 -0.910687, 115.250415 -0.8501919999999999, 115.204631 -0.796242, 115.151029 -0.750165, 115.090927 -0.713095, 115.025806 -0.685945, 114.957268 -0.669383, 114.887 -0.663816))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047939-251120083545085/datasets/export for details.
DOI: 10.34740/kaggle/dsv/14114198
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.8dkgju
title: Occurrence Download

description: A dataset containing 317 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Megascops marshalli",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 317 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047940-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8qr9f8
title: Occurrence Download

description: A dataset containing 275 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calibrachoa elegans"
 ]
}

 The dataset includes 275 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047941-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/kut74q
title: PAN-00002714 - coin/coin-related, Gallienus (253-268), antoninianus

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00002714&lt;/p&gt;
description: Modified: 2025-08-19T09:53:55+02:00
DOI: 10.26033/z0bp-je06
title: Friability of Meteorites Bundle

description: This bundle contains the complete experimental dataset and visual documentation from the friability analysis of seven meteorites: Richardton (H5), Tamdakht (H5), Zhob (H3/4), New Concord (L6), Allende (CV3), Murchison (CM2), and Aguas Zarcas (CM2). The dataset records the mass retained in each sieve bin after successive tumbling stages of 10, 100, 1,000, 10,000, and 100,000 revolutions, performed using the PTF-100 friability tester. All measurements were conducted according to the USP 1216 friability standard, using a 28.7 cm diameter drum that rotated at 25 rpm. Corresponding sieve sizes are 2000, 841, 400, 250, 177, 125, 63, 37, and 0.1. The data quantify the progressive mechanical disaggregation and redistribution of fragment sizes across increasing revolution counts, providing a quantitative basis for modeling the friability of meteorites. Seven chondritic meteorites representing diverse lithologies. The archive enables reproduction of all plots and calculations related to the evolution of friability as a bounded, multiplicative process, and provides a benchmark for linking laboratory comminution to asteroid surface processes.
DOI: 10.5281/zenodo.17712654
title: Database containing the simulation data used in 'Dynamical constraints on the S2 (S0-2) star possible companions'

description: The database contains the output of the N-body code TidyMESS (Boekholt & Correia, 2023) for simulations of S2-companion systems interacting with Sgr A*, the supermassive black hole at the center of the Galaxy. The dataset is provided as a single table encompassing all integration outputs produced by TidyMESS, optimized for use with SQL engines (e.g., PostgreSQL, MySQL) or Python-based equivalents such as SQLAlchemy.

Each row of the table corresponds to single simulation time-step of a given binary + Sgr A* system. The table columns are:



the identifier of the binary system (ID);

the simulation time (Time (yr));

the inertial position and velocity vectors of the SMBH (e.g., Inertial x-position BH (AU), Inertial x-velocity BH (AU/yr), etc.);

the inertial position and velocity vectors of the primary component (e.g., Inertial x-position primary (AU), Inertial x-velocity primary (AU/yr), etc.);

the inertial position and velocity vectors of the secondary component (e.g., Inertial x-position secondary (AU), Inertial x-velocity secondary (AU/yr), etc.);

the binary orbital parameters (Orbital period binary (day), Eccentricity, Cosine Mutual Inclination, and Mass ratio).


Using an SQL engine, users can retrieve specific systems, time intervals, or orbital quantities. For example, the first 10 time-steps of the integration for Binary 1 can be obtained with:

SELECT * FROM simulationWHERE "ID" = 'Binary 1'ORDER BY time_step ASCLIMIT 10; 

The N-body code TidyMESS, together with this dataset, also allows users to extend the dynamical evolution of any system. Surviving binaries can be evolved beyond the final simulation time used in the paper ('Dynamical constraints on the S2 (S0-2) star possible companions')  by setting the flag to_continue = 1 and adjusting t_end in the TidyMESS parameters file. In the case of merged or disrupted binaries, this flag may likewise be enabled to continue the evolution of the merged remnant or unbound components.
DOI: 10.5281/zenodo.17712655
title: Database containing the simulation data used in 'Dynamical constraints on the S2 (S0-2) star possible companions'

description: The database contains the output of the N-body code TidyMESS (Boekholt & Correia, 2023) for simulations of S2-companion systems interacting with Sgr A*, the supermassive black hole at the center of the Galaxy. The dataset is provided as a single table encompassing all integration outputs produced by TidyMESS, optimized for use with SQL engines (e.g., PostgreSQL, MySQL) or Python-based equivalents such as SQLAlchemy.

Each row of the table corresponds to single simulation time-step of a given binary + Sgr A* system. The table columns are:



the identifier of the binary system (ID);

the simulation time (Time (yr));

the inertial position and velocity vectors of the SMBH (e.g., Inertial x-position BH (AU), Inertial x-velocity BH (AU/yr), etc.);

the inertial position and velocity vectors of the primary component (e.g., Inertial x-position primary (AU), Inertial x-velocity primary (AU/yr), etc.);

the inertial position and velocity vectors of the secondary component (e.g., Inertial x-position secondary (AU), Inertial x-velocity secondary (AU/yr), etc.);

the binary orbital parameters (Orbital period binary (day), Eccentricity, Cosine Mutual Inclination, and Mass ratio).


Using an SQL engine, users can retrieve specific systems, time intervals, or orbital quantities. For example, the first 10 time-steps of the integration for Binary 1 can be obtained with:

SELECT * FROM simulationWHERE "ID" = 'Binary 1'ORDER BY time_step ASCLIMIT 10; 

The N-body code TidyMESS, together with this dataset, also allows users to extend the dynamical evolution of any system. Surviving binaries can be evolved beyond the final simulation time used in the paper ('Dynamical constraints on the S2 (S0-2) star possible companions')  by setting the flag to_continue = 1 and adjusting t_end in the TidyMESS parameters file. In the case of merged or disrupted binaries, this flag may likewise be enabled to continue the evolution of the merged remnant or unbound components.
DOI: 10.5281/zenodo.17500145
title: Russian Contentious Event Dataset (RCED)

description: RCED is a dataset of protest events that occurred in Russia between 2010 and 2023. It is built using Twitter (X) data and a combination of natural language processing techniques. The main file (RCED.csv or identical RCED.xlsx) contains all the event records. PROGOV, ANTIGOV, and NONPOL CSV files consist of events categorised by a fine-tuned GPT-3.5 model. Codebook.pdf provides detailed descriptions of each field. The entire process of data collection, along with its limitations, is described in the original article.
DOI: 10.5281/zenodo.17500460
title: Russian Contentious Event Dataset (RCED)

description: RCED is a dataset of protest events that occurred in Russia between 2010 and 2023. It is built using Twitter (X) data and a combination of natural language processing techniques. The main file (RCED.csv or identical RCED.xlsx) contains all the event records. PROGOV, ANTIGOV, and NONPOL CSV files consist of events categorised by a fine-tuned GPT-3.5 model. Codebook.pdf provides detailed descriptions of each field. The entire process of data collection, along with its limitations, is described in the original article.
DOI: 10.15468/dl.qhg75r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((110.466 -0.6488159999999999, 110.395732 -0.654383, 110.327194 -0.670945, 110.262073 -0.698095, 110.201972 -0.735165, 110.14837 -0.781243, 110.102587 -0.835193, 110.06575 -0.895688, 110.038766 -0.961238, 110.022301 -1.03023, 110.01676 -1.100966, 110.02228 -1.171703, 110.038727 -1.2407, 110.065695 -1.306258, 110.102522 -1.366762, 110.148302 -1.420723, 110.201908 -1.46681, 110.262019 -1.50389, 110.327155 -1.531047, 110.395712 -1.547614, 110.466 -1.553182, 110.536288 -1.547614, 110.604845 -1.531047, 110.669981 -1.50389, 110.730092 -1.46681, 110.783698 -1.420723, 110.829478 -1.366762, 110.866305 -1.306258, 110.893273 -1.2407, 110.90972 -1.171703, 110.91524 -1.100966, 110.909699 -1.03023, 110.893234 -0.961238, 110.86625 -0.895688, 110.829413 -0.835193, 110.78363 -0.781243, 110.730028 -0.735165, 110.669927 -0.698095, 110.604806 -0.670945, 110.536268 -0.654383, 110.466 -0.6488159999999999))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047942-251120083545085/datasets/export for details.
DOI: 10.15468/dl.7tgpsg
title: Occurrence Download

description: A dataset containing 32401283 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 32401283 records from 4511 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047895-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.