cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28597118
title: COVID-19 Seasonality Data

description: DOI: 10.1088/2752-5309/ad0320Abstract: The occurrence of cases of COVID-19 suggests that it will likely become seasonally endemic in human populations. We seek to provide a quantification of the seasonality of the occurrence and severity of COVID-19 cases in human populations. Using global data, we show that the spatiotemporal distribution of COVID-19 cases is a function of distinct seasons and climates. We investigated this at the county and the country scale using a comparison of seasonal means, correlation analyses using ambient air temperatures and dew point temperatures, and multiple linear regression techniques. We found that most locations had the highest incidence of COVID-19 during winter compared to other seasons. Regions closer to the equator had a higher incidence of COVID-19 during the summer than regions further from the equator. Regions close to the equator, where mean annual temperatures have less variance compared to those further from the equator, had smaller differences between seasonal COVID-19 incidence. Correlation and regression analyses showed that ambient air and dew point temperatures were significantly associated with COVID-19 incidence. Our results suggest that temperature and the environment are influential factors to understand the transmission of COVID-19 within the human population. This research provides empirical evidence that temperature changes are a strong indicator of seasonal COVID-19 outbreaks, and as such it will aid in planning for future outbreaks and for mitigating their impacts.
DOI: 10.5281/zenodo.15024627
title: Chinwa1/Standard_area_diagram: Standard area diagram DOI

description: Dataset for standard area diagram
DOI: 10.5281/zenodo.15024628
title: Chinwa1/Standard_area_diagram: Standard area diagram DOI

description: Dataset for standard area diagram
DOI: 10.5066/p99iaxui
title: Nitrogen Loads, Yields, and Associated Field Data Collected During Baseflow Conditions and Site Attributes for Small Basins Draining to Long Island Sound

description: During the spring and summer of 2022, the U.S. Geological Survey collected water-quality samples for nutrient analysis at 45 stations across the state of Connecticut and adjacent areas of New York and Rhode Island to better understand the groundwater discharge component of nitrogen loading to the Long Island Sound. The targeted stations were located in small drainage basins (less than 50 square kilometers) in the southern portion of the Long Island Sound watershed. Sites were selected randomly from groups based on expected drivers or controls on baseflow nitrogen loads. Factors used in the grouping included four metrics calculated for the upstream watershed: percent impervious cover, septic system density, percent agricultural or turf grass land cover, and percent coarse-grained stratified sediments. The water-quality samples and instantaneous discharge measurements were collected under baseflow conditions during two separate synoptic sampling events, one in the nongrowing season (April 2022) and one in the growing season (June and July 2022). Instantaneous discharge measurements were collected in addition to water-quality samples to enable the calculations of nitrogen loads and yields. The water-quality samples were analyzed for physical properties and concentrations of chloride, nutrient species, and dissolved organic carbon; some analyses were performed past analytical method holding times. This data release includes site characteristics and geospatial data for potential and final (selected) sites, as well as field data, analytical results, and calculated nitrogen loads and yields for the final sites. Column names, units and descriptions are provided in data_dictionary.txt and a lookup table for method codes is provided in MethodLookupTable.txt. Note that many station identifiers (site_no) have a leading &quot;0&quot; that should be retained.
DOI: 10.12751/g-node.kv2mlt
title: Large-scale infra-slow dynamics of extracellular potentials linked to synchronous states revealed by graphene neural probes

description: Large-scale multiplexed graphene transistors arrays show DC-coupled recording capabilities, enabling to study the coupling between infra-slow dynamics
and oscillatory states with high spatio-temporal resolution in freely moving animals. The movies in this repository show examples of the infra-slow to 
low-gamma dynamics recorded with these micro-electrocorticography arrays.
description: IsSupplementTo: Ramon Garcia-Cortadella et al.: Large-scale infra-slow dynamics of extracellular potentials linked to synchronous states revealed by graphene neural probes. Under Review.
description: IsSupplementTo: Garcia-Cortadella et al. (2024) Large-scale infra-slow dynamics of extracellular potentials linked to synchronous states revealed by graphene neural probes. bioRxiv. https://doi.org/10.1101/2024.12.20.629545
DOI: 10.5284/1122726
title: Data from an Archaeological Mitigation at Coleshill Moat and Gardens, Coleshill, Warwickshire, 2020-2022 (HS2 Phase One)

description: This collection comprises digital data (images, text, spreadsheets, GIS, vector graphics, photogrammetry and laser scanning models, and videos) from a programme of archaeological investigations at Coleshill Moat and Gardens, Coleshill, Warwickshire, between July 2020 and December 2022.
DOI: 10.15468/dl.zy3jcq
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Armeria colorata Pau"
 ]
}

 The dataset includes 102 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008768-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e222884
title: ECIN Replication Package for Why do Peers Influence College Major Selection?

description: This archive contains code and synthetic data to generate results for the linked manuscript. Manuscript abstract is below:<br><br>Why do peers influence people’s choices? Is it for information (social learning) or for socializing (social utility)? Exploiting unique data and natural experiments from the United States Naval Academy (USNA), we analyze data on major selections of USNA students. We find peers influence students into selecting different academic paths than they would have chosen independently. Through random reassignments, “shot-guns”, of students into new peer groups along with random assignments into courses, we explore the reasons why herding occurs. Evidence suggests that social learning, as opposed to social utility, is an important driver for herding behavior.
description: Original datasets are proprietary. Archive includes synthetic versions of the original data that can be used to operationalize the code that generates manuscript results. Instructions for access to original data are included within this archive.
DOI: 10.15468/dl.7kkbgd
title: Occurrence Download

description: A dataset containing 610859 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trifolium pratense L.",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 2010"
 ]
}

 The dataset includes 610859 records from 1468 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008757-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q6mp8v
title: Occurrence Download

description: A dataset containing 990 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nathrius brevipennis (Mulsant, 1839)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 990 records from 123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008769-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.30346
title: location filter
title: location filter

description: Screening of latitudes and longitudes with offshore distances of 5-53 km and water depths of 5-200 m
description: Screening of latitudes and longitudes with offshore distances of 5-53 km and water depths of 5-200 m
DOI: 10.6084/m9.figshare.30445532
title: Data and code for the 2025 Jiang et al.<i> </i>paper

description: This repository contains all data and code necessary to replicate the analyses reported in the manuscript. The dataset includes contributor-level information, pull request records, and activity events. The code files provide scripts for data preprocessing, statistical modeling, and figure generation. Detailed instructions are included in the README.md file to ensure reproducibility.
DOI: 10.6084/m9.figshare.30445532.v1
title: Data and code for the 2025 Jiang et al.<i> </i>paper

description: This repository contains all data and code necessary to replicate the analyses reported in the manuscript. The dataset includes contributor-level information, pull request records, and activity events. The code files provide scripts for data preprocessing, statistical modeling, and figure generation. Detailed instructions are included in the README.md file to ensure reproducibility.
DOI: 10.15468/dl.h68vwh
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Microtus sachalinensis"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001781-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.30352
title: 16S rRNA gene sequences of rice paddy soils from Amol and Neka
title: 16S rRNA gene sequences of rice paddy soils from Amol and Neka

description: Soils were sampled during 2021 from 2 paddy fields located in Amol and Neka, and transported to the laboratory. A microcosm experiment was conducted to systematically evaluate the hierarchical influence of HP, CSP, and TS on pesticide dissipation and microbial community dynamics. DNA was extracted from the paddy soils, and the V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified and sequenced using the Illumina MiSeq v3 platform.
description: Soils were sampled during 2021 from 2 paddy fields located in Amol and Neka, and transported to the laboratory. A microcosm experiment was conducted to systematically evaluate the hierarchical influence of HP, CSP, and TS on pesticide dissipation and microbial community dynamics. DNA was extracted from the paddy soils, and the V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified and sequenced using the Illumina MiSeq v3 platform.
DOI: 10.57760/sciencedb.30399
title: The three-directional six-DOF seismic simulation shaking table simulates sinusoidal motion, random vibration, and seismic records.
title: 三向六自由度地震模拟振动台模拟正弦运动、随机振动和地震波记录

description: In Matlab, the simulated control system of a three-way six degree of freedom vibration table is designed by inputting relevant sine motion signals, random wave signals, and EI centtor signals for simulation to verify whether the control system of the vibration table meets the design requirements. Upload the data code for this generated chart here. for reference 
description: In Matlab, the simulated control system of a three-way six degree of freedom vibration table is designed by inputting relevant sine motion signals, random wave signals, and EI centtor signals for simulation to verify whether the control system of the vibration table meets the design requirements. Upload the data code for this generated chart here. for reference
DOI: 10.57760/sciencedb.30347
title: Calculation of power generation and carbon reduction
title: Calculation of power generation and carbon reduction

description: 光伏组件发电量计算及减碳量
description: 光伏组件发电量计算及减碳量
DOI: 10.57760/sciencedb.30448
title: Experimental and modeling study on process parameters and geometric features for WLAM
title: Experimental and modeling study on process parameters and geometric features for WLAM

description: This dataset is for the reseach on "Developing high-precision and interpretable model from small dataset for process parameters in wire laser additive manufacturing". It include vast experimental study, response surface methodology modeling and machine learning modeling data. Who want to cite or carry on deeper research based on this dataset, please contact with the author.
description: This dataset is for the reseach on "Developing high-precision and interpretable model from small dataset for process parameters in wire laser additive manufacturing". It include vast experimental study, response surface methodology modeling and machine learning modeling data. Who want to cite or carry on deeper research based on this dataset, please contact with the author.
DOI: 10.34740/kaggle/dsv/13513809
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.5f2x46
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new freshwater goby of Rhinogobius lingtongyanensis (Teleostei, Gobiidae) from the Dongshi river basin, Fujian Province, southeastern China"
 ]
}

 The dataset includes 29 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001782-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xy3snm
title: Occurrence Download

description: A dataset containing 271358 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November, December)",
 "OccurrenceStatus is Present",
 "Year is 2010"
 ]
}

 The dataset includes 271358 records from 334 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001765-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9s5nc
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new freshwater goby of Rhinogobius Gill, 1859 (Teleostei, Gobiidae) from the Jangshi basin, Fujian Province, southeastern China"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001784-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r588qv
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Microtus sachalinensis"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001785-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17451896
title: Calibrated ML and Decision-Curve Analysis for Passenger-Service Operations

description: Overview

This repository accompanies the manuscript **“From Probabilities to Workload: Calibrated ML and Decision-Curve Analysis for Passenger-Service Operations”** (submitted to the *International Journal of Transportation Science and Technology*). It provides a **fully reproducible pipeline** for training, calibrating, and evaluating machine‑learning models for airline passenger‑service operations, with a direct translation from **calibrated risk** to **operational workload** (alerts/day, TP/FP/day) using **Decision‑Curve Analysis (DCA)** within an operational policy window.


Contents

- `code/` — Python source (data pipeline, model training, isotonic calibration, metrics: Brier/Murphy/ECE, DCA, explainability).

- `configs/` — YAML configuration and schema files (frozen preprocessing; leakage‑controlled splits).

- `artifacts/` — Derived artifacts: model binaries, predictions, logs, figures, and tables referenced in the manuscript.

- `runbook.md` — Minimal commands to reproduce the main results end‑to‑end.

- `environment.txt` — Pinned Python versions / key dependencies for reproducibility.

- `LICENSE` — Open‑source license for the code (MIT recommended).

- `CITATION.cff` — How to cite this repository.

- `README.md` — Quick start and usage notes.


Data: This deposit includes *derived* artifacts only. The raw passenger dataset is publicly available from the original provider and should be obtained directly by users following the instructions in `README.md`. All paths/commands assume the raw data are placed under `data/raw/` as described in the runbook.


Methods snapshot

- Models: regularized logistic regression, random forests, and gradient‑boosting trees; probabilities calibrated with **isotonic regression**.

- Reliability: **Brier score** with **Murphy decomposition** (Reliability/Resolution/Uncertainty) and **Expected Calibration Error (ECE)**.

- Decision impact: **Net benefit / Decision‑Curve Analysis** in a policy window; translation to workload per operational segment (cabin class, distance, delay band, travel type).
DOI: 10.5281/zenodo.17451897
title: Calibrated ML and Decision-Curve Analysis for Passenger-Service Operations

description: Overview

This repository accompanies the manuscript **“From Probabilities to Workload: Calibrated ML and Decision-Curve Analysis for Passenger-Service Operations”** (submitted to the *International Journal of Transportation Science and Technology*). It provides a **fully reproducible pipeline** for training, calibrating, and evaluating machine‑learning models for airline passenger‑service operations, with a direct translation from **calibrated risk** to **operational workload** (alerts/day, TP/FP/day) using **Decision‑Curve Analysis (DCA)** within an operational policy window.


Contents

- `code/` — Python source (data pipeline, model training, isotonic calibration, metrics: Brier/Murphy/ECE, DCA, explainability).

- `configs/` — YAML configuration and schema files (frozen preprocessing; leakage‑controlled splits).

- `artifacts/` — Derived artifacts: model binaries, predictions, logs, figures, and tables referenced in the manuscript.

- `runbook.md` — Minimal commands to reproduce the main results end‑to‑end.

- `environment.txt` — Pinned Python versions / key dependencies for reproducibility.

- `LICENSE` — Open‑source license for the code (MIT recommended).

- `CITATION.cff` — How to cite this repository.

- `README.md` — Quick start and usage notes.


Data: This deposit includes *derived* artifacts only. The raw passenger dataset is publicly available from the original provider and should be obtained directly by users following the instructions in `README.md`. All paths/commands assume the raw data are placed under `data/raw/` as described in the runbook.


Methods snapshot

- Models: regularized logistic regression, random forests, and gradient‑boosting trees; probabilities calibrated with **isotonic regression**.

- Reliability: **Brier score** with **Murphy decomposition** (Reliability/Resolution/Uncertainty) and **Expected Calibration Error (ECE)**.

- Decision impact: **Net benefit / Decision‑Curve Analysis** in a policy window; translation to workload per operational segment (cabin class, distance, delay band, travel type).
DOI: 10.15468/dl.3epe4c
title: Occurrence Download

description: A dataset containing 7898 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erithacus rubecula",
 "Year 1910-1955"
 ]
}

 The dataset includes 7898 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001786-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6m2kv3
title: Occurrence Download

description: A dataset containing 1468203 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Polygonia c-album",
 "Year 1980-2025"
 ]
}

 The dataset includes 1468203 records from 2633 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001770-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive21813.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089274.10fu
title: SH0089274.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive21813.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089275.10fu
title: SH0089275.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.