cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.rtk4cg
title: Occurrence Download

description: A dataset containing 6252 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Melandrya caraboides (Linnaeus, 1760), Monochamus sutor (Linnaeus, 1758), Onthophagus coenobita (Herbst, 1783))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 6252 records from 207 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0156442-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kuhkgk
title: Occurrence Download

description: A dataset containing 5904 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-180 66,180 66,180 90,-180 90,-180 66))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anthriscus sylvestris (L.) Hoffm."
 ]
}

 The dataset includes 5904 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0147668-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v5t4ia
title: Occurrence Download

description: A dataset containing 7273 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mentha ×piperita L."
 ]
}

 The dataset includes 7273 records from 324 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028607-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.887fsz
title: Occurrence Download

description: A dataset containing 3914 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anastrangalia dubia (Scopoli, 1763), Ancistronycha abdominalis (Fabricius, 1798))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 3914 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0156007-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7aocml
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aloe mawii Christian"
 ]
}

 The dataset includes 42 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020832-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qacmgg
title: Occurrence Download

description: A dataset containing 323 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is China",
 "Country is Chinese Taipei",
 "Country is Hong Kong",
 "Country is Macao"
 ]
 },
 "TaxonKey is Imperata cylindrica var. major (Nees) C.E.Hubb."
 ]
}

 The dataset includes 323 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265250-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.amrgzt
title: Occurrence Download

description: A dataset containing 11255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Lutra lutra (Linnaeus, 1758)"
 ]
}

 The dataset includes 11255 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013023-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8th5r6
title: Occurrence Download

description: A dataset containing 19741 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is AIMSurv Aedes Invasive Mosquito species harmonized surveillance in Europe. AIM-COST Action"
 ]
}

 The dataset includes 19741 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0418808-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jtgc2d
title: Occurrence Download

description: A dataset containing 3578 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "TaxonKey is Fratercula arctica (Linnaeus, 1758)",
 "StateProvince is England",
 "Year 2000-2020"
 ]
}

 The dataset includes 3578 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040993-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f2jpqf
title: Occurrence Download

description: A dataset containing 7590 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anisodactylus binotatus (Fabricius, 1787), Anomala vitis (Fabricius, 1775))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 7590 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0156014-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/mxt4-b075
title: NOAA/NCEI Blended Global Sea Surface Winds, Version 2
DOI: 10.15468/dl.xpd5ea
title: Occurrence Download

description: A dataset containing 6595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-113.71658 64.47408,-108.31118 64.47408,-108.31118 68.77153,-113.71658 68.77153,-113.71658 64.47408))",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 6595 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026912-240626123714530/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.26264096
title: Patient preferences for primary cardiovascular care in Quebec [Discrete choice experiment]

description: Cardiovascular diseases and their risk factors are leading causes of morbidity and mortality worldwide, and are among the top reasons for primary care visits. Little is known about patient preferences for primary care in the context of chronic conditions. This study aimed to investigate the effect of key organizational features identified by patients and providers on patients’ choice of a preferred primary care practice to receive cardiovascular care.A discrete choice experiment survey was completed by a weighted online sample of Quebec residents aged 35 and over, and having or being at risk of cardiovascular disease (with hypertension, dyslipidemia, or diabetes excluding gestational diabetes). Respondents completed one of two blocks of nine choice sets by indicating, among three hypothetical primary care practice alternatives in each choice set, their preferred and second-most preferred options. Alternatives were differentiated on the basis of five key attributes that were identified as priorities in an earlier Delphi study: 1) listening to and respecting care preferences; 2) providing personalized information; 3) 24-to-48-hour accessibility in the event of a problem; 4) continuity of care; and 5) up-to-date clinical skills. Each attribute could be assigned a high, moderate or low level. After the discrete choice experiment, perceived task difficulty was assessed by using a standard user metric known as the Single Ease Question, a 7-point rating scale from 1-“very difficult” to 7-“very easy”. Respondents also answered sociodemographic and health-related questions, most of which were taken from the Canadian Community Health Survey, an annual cross-sectional survey from Canada’s national statistical office. Health literacy was measured by using the BRIEF Health Literacy Screening Tool, and readiness to change lifestyle was measured using 1-to-10 Readiness Rulers.The study was approved by the University of Montreal Hospital Research Centre’s research ethics committee (project number 17.305). Data collection took place from November 5 to November 12, 2021 and was stopped after 501 completed questionnaires were obtained.
DOI: 10.6084/m9.figshare.26264096.v1
title: Patient preferences for primary cardiovascular care in Quebec [Discrete choice experiment]

description: Cardiovascular diseases and their risk factors are leading causes of morbidity and mortality worldwide, and are among the top reasons for primary care visits. Little is known about patient preferences for primary care in the context of chronic conditions. This study aimed to investigate the effect of key organizational features identified by patients and providers on patients’ choice of a preferred primary care practice to receive cardiovascular care.A discrete choice experiment survey was completed by a weighted online sample of Quebec residents aged 35 and over, and having or being at risk of cardiovascular disease (with hypertension, dyslipidemia, or diabetes excluding gestational diabetes). Respondents completed one of two blocks of nine choice sets by indicating, among three hypothetical primary care practice alternatives in each choice set, their preferred and second-most preferred options. Alternatives were differentiated on the basis of five key attributes that were identified as priorities in an earlier Delphi study: 1) listening to and respecting care preferences; 2) providing personalized information; 3) 24-to-48-hour accessibility in the event of a problem; 4) continuity of care; and 5) up-to-date clinical skills. Each attribute could be assigned a high, moderate or low level. After the discrete choice experiment, perceived task difficulty was assessed by using a standard user metric known as the Single Ease Question, a 7-point rating scale from 1-“very difficult” to 7-“very easy”. Respondents also answered sociodemographic and health-related questions, most of which were taken from the Canadian Community Health Survey, an annual cross-sectional survey from Canada’s national statistical office. Health literacy was measured by using the BRIEF Health Literacy Screening Tool, and readiness to change lifestyle was measured using 1-to-10 Readiness Rulers.The study was approved by the University of Montreal Hospital Research Centre’s research ethics committee (project number 17.305). Data collection took place from November 5 to November 12, 2021 and was stopped after 501 completed questionnaires were obtained.
DOI: 10.17632/7mgj5bvp5h.1
title: Papaya Freshness Classification Dataset

description: This dataset has labelled images of bad and good of Papaya (Carica Papaya). Each class contains 500 images.
DOI: 10.15468/dl.kbnw6r
title: Occurrence Download

description: A dataset containing 349 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Antarctica",
 "TaxonKey is Balaenoptera physalus (Linnaeus, 1758)"
 ]
}

 The dataset includes 349 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026914-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nn8prk
title: Occurrence Download

description: A dataset containing 98036 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "WaterBody is North Sea"
 ]
}

 The dataset includes 98036 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026913-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2y538xxs2w.1
title: Good and Bad classification of Brassica Oleracea flower (Cauliflower)

description: For the project titled "Good and Bad Classification of Brassica oleracea Flower (Cauliflower)," a comprehensive dataset has been compiled containing 1,000 samples of Marsh Barbel Leaves, equally divided into 500 good samples and 500 bad samples. This dataset serves as the foundation for developing a classification model aimed at distinguishing between good and bad samples of cauliflower flowers based on their associated Marsh Barbel Leaves.

### Data Description

The dataset comprises the following key features:

1. *Image Data*:
 - Each sample includes high-resolution images of Marsh Barbel Leaves.
 - Images are standardized in terms of resolution and format to ensure consistency.
 - Various angles and lighting conditions are considered to mimic real-world scenarios.

2. *Leaf Quality Label*:
 - Each image is annotated with a binary label indicating its quality:
 - 0 for bad samples.
 - 1 for good samples.
 - Labels are determined by expert agronomists to ensure accuracy.

3. *Visual Attributes*:
 - *Color*: Variations in leaf color, ranging from healthy green to diseased yellow or brown, are noted.
 - *Texture*: Differences in leaf surface texture, including signs of wilting or crispness.
 - *Shape*: Anomalies in leaf shape, such as irregular edges or deformities.
 - *Spots and Lesions*: Presence of spots, lesions, or other visible signs of disease or pest infestation.

4. *Metadata*:
 - *Capture Date and Time*: Timestamp for when each image was captured.
 - *Location*: Geographical data indicating where the leaf samples were collected.
 - *Weather Conditions*: Environmental factors at the time of capture, which might influence leaf quality.
 - *Growth Stage*: The developmental stage of the cauliflower plant, which can impact leaf appearance.

### Data Collection and Preprocessing

1. *Collection Method*:
 - Leaves were collected from various cauliflower fields to ensure diversity in the dataset.
 - Images were taken using high-resolution cameras under controlled conditions.

2. *Preprocessing Steps*:
 - *Image Normalization*: All images are resized to a uniform dimension to facilitate model training.
 - *Data Augmentation*: Techniques such as rotation, flipping, and scaling are applied to increase the dataset's variability and robustness.
 - *Label Encoding*: Quality labels are encoded as binary values to simplify the classification task.

### Dataset Utilization

This dataset is intended to train and evaluate machine learning models for the classification of Marsh Barbel Leaves quality, which indirectly assesses the health of Brassica oleracea flowers (cauliflower). The ultimate goal is to develop a reliable system that can aid farmers and agronomists in early detection of diseases or deficiencies in cauliflower crops, leading to timely interventions and improved crop yield.

### Potential Applications

- *Automated Crop Monitoring*: Integration of the model into automated systems for continuous mon
DOI: 10.25574/01117
title: Chandra X-ray Observatory ObsId 01117
DOI: 10.17632/jfbp52dmv7.1
title: Good and bad classification of Betel leaf (Piper Betel)

description: ## Data Description for Good and Bad Classification of Betel Leaf (Piper Betel)

### Introduction
The dataset comprises 1000 samples of Marsh Barbel Leaves, specifically of the Betel leaf (Piper Betel) variety. This dataset is evenly divided into two categories: 500 good samples and 500 bad samples. The goal of this project is to develop a classification model that can accurately distinguish between good and bad Betel leaves based on the provided features.

### Dataset Composition
1. *Total Samples*: 1000
 - *Good Samples*: 500
 - *Bad Samples*: 500

### Features
The dataset includes various features that are crucial for determining the quality of Betel leaves. These features can be broadly categorized into visual, physical, and chemical characteristics. Below is a detailed description of the features included:

1. *Visual Characteristics*
 - *Color*: The RGB values representing the color of the leaf.
 - *Texture*: Numerical representation of the leaf's texture, obtained through image processing techniques.
 - *Shape*: Features related to the shape, such as area, perimeter, and aspect ratio.
 - *Defects*: Binary or categorical indicators of visual defects like spots, discoloration, or holes.

2. *Physical Characteristics*
 - *Size*: Measured dimensions of the leaf, such as length and width.
 - *Weight*: The mass of the leaf, recorded in grams.

3. *Chemical Characteristics*
 - *Moisture Content*: Percentage of water content in the leaf.
 - *Chlorophyll Level*: Measured chlorophyll content, indicating the leaf's health.
 - *Nutrient Levels*: Concentration of essential nutrients like nitrogen, phosphorus, and potassium.

### Data Collection
The data has been collected from various sources, including agricultural research centers, farms, and markets. Each sample has been meticulously labeled by experts to ensure accuracy. Advanced imaging techniques and sensors were employed to capture the visual and physical characteristics, while laboratory analyses were conducted to determine the chemical properties.

### Data Format
The dataset is provided in a tabular format, with each row representing a single leaf sample. The columns correspond to the different features and the label (good or bad). Below is a sample structure of the dataset:

| Sample ID | Color_R | Color_G | Color_B | Texture | Shape_Area | Shape_Perimeter | Shape_Aspect_Ratio | Defects | Length | Width | Weight | Moisture_Content | Chlorophyll_Level | Nitrogen_Level | Phosphorus_Level | Potassium_Level | Label |
|-----------|---------|---------|---------|---------|-------------|-------

### Usage
This dataset is intended for use in developing machine learning models for the classification of Betel leaves. Researchers and developers can employ various algorithms, such as decision trees, support vector machines, or neural networks, to train and validate models. The balanced nature of the dataset ensures that models can be trained without bias towards any particular class
DOI: 10.15468/dl.zw3d4a
title: Occurrence Download

description: A dataset containing 2679 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hygrocybe conica (Schaeff.) P.Kumm."
 ]
}

 The dataset includes 2679 records from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026915-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dsvzj4yvyc.1
title: relationship between PFASs and prediabetes

description: The dataset includes raw data and codes for single and combined effect dose-response relationships.
DOI: 10.57745/iuekuz
title: 202402121303_60_25_net.zip

description: :unav
DOI: 10.57745/trl0zh
title: 20240124_60_30_nonet.zip

description: :unav
DOI: 10.57745/6337at
title: 202402121315_60_0_nonet.zip

description: :unav
DOI: 10.57745/cdgftw
title: simu_data_0_nonet.zip

description: :unav
DOI: 10.57745/jl9qcf
title: 20240202_60_net_a1_0_a2_25.zip

description: :unav
DOI: 10.57745/lerttk
title: simu_data_0_17.zip

description: :unav
DOI: 10.57745/ts9yjr
title: 202402121259_60_0_net.zip

description: :unav
DOI: 10.57745/v3as1u
title: simu_data_30_nonet.zip

description: :unav
DOI: 10.57745/hxxpiy
title: simu_data_30.zip

description: :unav
DOI: 10.57745/sec5ck
title: simu_data_0.zip

description: :unav
DOI: 10.57745/xw6fy5
title: codes.zip

description: :unav
DOI: 10.15468/dl.x7bnj5
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "DatasetKey is one of (UCM Amphibian and Reptile Collection (Arctos), Sistemática e historia natural de algunos anfibios y reptiles de México)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is one of (4cadac10-3e7b-11d9-8439-b8a03c50a862, ff90b050-c256-11db-b71b-b8a03c50a862)",
 "TaxonKey is Sceloporus halli Dasmann & Smith, 1974",
 "Year 1950-2024"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026917-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.