cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28309166
title: Supplementary Material for: Investigation of risk factors and development and validation of a nomogram for predicting overall survival in breast invasive lobular carcinoma

description: Objective: Invasive lobular carcinoma (ILC) of breast is a common pathological subtype of breast cancer, ranks second in terms of incidence rate following invasive ductal carcinoma. The aim of this study is to construct a nomogram for predicting overall survival (OS) in patients with ILC and to identify risk factors that affect their survival prognosis.
Methods: The patients diagnosed with ILC between 2010 and 2015 were extracted from Surveillance, Epidemiology, and End Results (SEER) database. They were randomly split into a training set with 18365 samples for model training and parameter tuning, and a validation set with 7872 samples for independent accuracy verification. The independent risk factors were screened by Lasso regression and multivariable Cox regression. A nomogram was constructed for the 3-year, 5-year, and 10-year overall survival rates based on these independent risk factors. Model efficiency was assessed through Harrell’s concordance index (C-index), Calibration curves, Receiver operating characteristic (ROC) curves and decision curve analysis (DCA).
Results: A total of 26,237 patients diagnosed with ILC were include. The following factors were identified as independent risk factors associated with OS: Age, Marital status, Grade, Estrogen receptor (ER), Progesterone receptor (PR), Surgery, Radiation therapy, and Tumor size(T), Lymph Node (N), and Metastasis (M) stages. The C-index was 0.795 in the training set, while in the validation set it was 0.791. The corresponding Area Under Curves (AUC) for 3-year, 5-year, and 10-year were 0.837, 0.828, and 0.791 in the training set, and 0.832, 0.826 and 0.781 in the validation set, respectively. The calibration curve of the nomogram showed good consistency, and the DCA curves also suggested that it can provide valuable guidance for clinical decision making.
Conclusions: The established nomogram predicting 3-year, 5-year, and 10-year OS for patients with ILC showed a good performance and it can help clinicians make more favorable clinical decisions.
DOI: 10.6096/parcs.13
title: Snow pit Austre Lovenbren 2012

description: Sampling in a snow pit to measure physical and chemical snow properties
DOI: 10.7289/v5ht2m8t
title: NOAA Climate Data Record (CDR) of Cloud and Clear-Sky Radiation Properties, Version 1.0

description: The NASA LaRC cloud and clear sky radiation properties dataset is generated using algorithms initially developed for application to TRMM and MODIS imagery within the NASA CERES program. The algorithms have been adapted to operate upon AVHRR, an instrument that has fewer spectral channels than MODIS. This dataset utilizes calibrated AVHRR reflectances from a companion FCDR. Cloud and clear-sky radiation properties are derived globally at the 4 km Global Area Coverage pixel scale during both day and night using this approach. CDR quality variables include: Cloud and clear sky pixel detection (count), Cloud top thermodynamic phase (count), Cloud optical depth (count), Cloud particle effective radius (micrometers), Air pressure at effective cloud top (hPa), Air temperature at effective cloud top (K), and Height at effective cloud top (km). Other Non-CDR Quality Variables include: Air pressure at cloud top (hPa), Air temperature at cloud top (K), Height at cloud top (km), Height at cloud base (km), Air pressure at cloud base (hPa), Overshooting cloud top detection mask (count), Land and sea surface temperature retrieval (K), Shortwave broadband albedo (unit less), Longwave broadband flux (W/m2), Snow and ice cover flag (count), Land and sea surface temperature retrieval quality flag (count), Clear sky pixel classification (count), Cloudy pixel classification (count)
DOI: 10.7488/ds/2833
title: SUPERSEDED - Data supporting the manuscript "A climate-dependent global model of ammonia emissions from chicken farming"

description: ## SUPERSEDED - This item has been replaced by the one which can be found at https://doi.org/10.7488/ds/2936 ##. This dataset contains files of ammonia emissions from global chicken agriculture, from chicken housing to land spreading of chicken manure. All files are in netCDF format and can be easily read and processed by Python packages, e.g. Xarray or netCDF4. More details can be read from the files. Please note that these files are to support the manuscript submitted to the Journal Biogeosciences, and may be edited under peer-review processes. Any inquiries go to Jize.Jiang@ed.ac.uk Broiler_file.nc: ammonia emission and volatilisation rate from broiler housing Layer_file.nc: ammonia emission and volatilisation rate from layer housing bc_file.nc: ammonia emission and volatilisation rate from backyard chicken barley NH3.nc: ammonia emission and volatilisation rate from fertilising barley maize NH3.nc: ammonia emission and volatilisation rate from fertilising maize potato NH3.nc: ammonia emission and volatilisation rate from fertilising potato rice NH3.nc: ammonia emission and volatilisation rate from fertilising rice sugarbeet NH3.nc: ammonia emission and volatilisation rate from fertilising sugarbeet wheat NH3.nc: ammonia emission and volatilisation rate from fertilising wheat
DOI: 10.11588/data/7qcr8s
title: Deep learning for the detection of anatomical tissue structures and neoplasms of the skin on scanned histopathological tissue sections [data]

description: Basal cell carcinoma (BCC), squamous cell carcinoma (SqCC) and melanoma are among the most common cancer types. Correct diagnosis based on histological evaluation after biopsy or excision is paramount for adequate therapy stratification. Deep learning on histological slides has been suggested to complement and improve routine diagnostics. Publicly available curated and annotated data and usable models trained to distinguish common skin tumors are rare and often lack heterogeneous non-tumor categories. A total of 16 classes from 386 cases were manually annotated on scanned histological slides, 129364 100 x 100 µm (395 x 395 px) image tiles were extracted and split into a training, validation and test set. An EfficientV2 neuronal network was trained and optimized to classify image categories. Cross entropy loss, balanced accuracy and Matthews correlation coefficient were used for model evaluation. Image and patient data were assessed with confusion matrices. Application of the model to an external set of whole slides facilitated tumor localization. Automated differentiation of BCC, SqCC, melanoma, naevi and non-tumor tissue structures was possible, and a high diagnostic accuracy was achieved in the validation (98%) and test (97%) set. In summary, we provide a curated dataset including the most common neoplasms of the skin and various anatomical compartments to enable researchers to train, validate and improve deep learning models. Automated classification of skin tumors by deep learning techniques is possible with high accuracy, facilitates tumor localization and has the potential to support and improve routine diagnostics.
DOI: 10.13026/c2qg6q
title: The Long-Term AF Database

description: This database includes 84 long-term ECG recordings of subjects with paroxysmal or sustained atrial fibrillation (AF). Each record contains two simultaneously recorded ECG signals digitized at 128 Hz with 12-bit resolution over a 20 mV range; record durations vary but are typically 24 to 25 hours.
DOI: 10.13117/central-america-caribbean-active-faults
title: GEM Central America and Caribbean Active Faults Database
DOI: 10.14291/tccon.ggg2014.bialystok01.r2
title: TCCON data from Bialystok (PL), Release GGG2014.R2

description: The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers that record direct solar absorption spectra of the atmosphere in the near-infrared. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This data set contains observations from the TCCON station at Bialystok, Poland.
description: <br>Cite this record as:<br>Deutscher, N. M., Notholt, J., Messerschmidt, J., Weinzierl, C., Warneke, T., Petri, C., & Grupe, P. (2019). <i>TCCON data from Bialystok (PL), Release GGG2014.R2</i> (Version R2) [Data set]. CaltechDATA. https://doi.org/10.14291/TCCON.GGG2014.BIALYSTOK01.R2<br> or choose a different citation style.<br>Download Citation<br>
description: <br>Unique Views: 141<br>Unique Downloads: 8<br> between October 21, 2019 and July 12, 2021<br>More info on how stats are collected<br>
DOI: 10.14291/tccon.ggg2014.rikubetsu01.r2
title: TCCON data from Rikubetsu (JP), Release GGG2014.R2

description: The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers that record direct solar absorption spectra of the atmosphere in the near-infrared. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This data set contains observations from the TCCON station at Rikubetsu, Japan.
description: <br>Cite this record as:<br>Morino, I., Yokozeki, N., Matsuzaki, T., & Horikawa, M. (2018). <i>TCCON data from Rikubetsu (JP), Release GGG2014.R2</i> (Version R2) [Data set]. CaltechDATA. https://doi.org/10.14291/TCCON.GGG2014.RIKUBETSU01.R2<br> or choose a different citation style.<br>Download Citation<br>
description: <br>Unique Views: 327<br>Unique Downloads: 16<br> between June 06, 2018 and July 12, 2021<br>More info on how stats are collected<br>
DOI: 10.14291/tccon.ggg2014.tsukuba02.r2
title: TCCON data from Tsukuba (JP), 125HR, Release GGG2014.R2

description: The Total Carbon Column Observing Network (TCCON) is a network of ground-based Fourier Transform Spectrometers that record direct solar absorption spectra of the atmosphere in the near-infrared. From these spectra, accurate and precise column-averaged abundances of atmospheric constituents including CO2, CH4, N2O, HF, CO, H2O, and HDO, are retrieved. This data set contains observations from the TCCON station at Tsukuba, Japan.
description: <br>Cite this record as:<br>Morino, I., Matsuzaki, T., & Horikawa, M. (2018). <i>TCCON data from Tsukuba (JP), 125HR, Release GGG2014.R2</i> (Version R2) [Data set]. CaltechDATA. https://doi.org/10.14291/TCCON.GGG2014.TSUKUBA02.R2<br> or choose a different citation style.<br>Download Citation<br>
description: <br>Unique Views: 363<br>Unique Downloads: 27<br> between June 06, 2018 and July 12, 2021<br>More info on how stats are collected<br>
DOI: 10.15138/g3059z
title: Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957-2015; obspack_co2_1_GLOBALVIEWplus_v2.1_2016-09-02

description: This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products. This product includes 264 atmospheric carbon dioxide and 6 atmospheric water vapor records derived from observations made by 40 laboratories from 19 countries. Data for the period 1957-2015 (where available) are included.
DOI: 10.1594/pangaea.319921
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_08
DOI: 10.1594/pangaea.326883
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_03
DOI: 10.1594/pangaea.326886
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_06
DOI: 10.1594/pangaea.326888
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_09
DOI: 10.1594/pangaea.326889
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_10
DOI: 10.1594/pangaea.326890
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_11
DOI: 10.1594/pangaea.326892
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_13
DOI: 10.1594/pangaea.326897
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_18
DOI: 10.1594/pangaea.326898
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_19
DOI: 10.1594/pangaea.326899
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_20
DOI: 10.1594/pangaea.326901
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_22
DOI: 10.1594/pangaea.326902
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_23
DOI: 10.1594/pangaea.326903
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_24
DOI: 10.1594/pangaea.326904
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_25
DOI: 10.1594/pangaea.326906
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_27
DOI: 10.1594/pangaea.326907
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_28
DOI: 10.1594/pangaea.326909
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_30
DOI: 10.1594/pangaea.326910
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_31
DOI: 10.1594/pangaea.326913
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_34
DOI: 10.1594/pangaea.326915
title: Helicopter-borne sea ice thickness measurements during campaign IRIS2004 from flight IRIS2004_36
DOI: 10.1594/pangaea.760097
title: Seal census raw data during campaign EMAGE-I
DOI: 10.1594/pangaea.760098
title: Seal census raw data during campaign EMAGE-II
DOI: 10.1594/pangaea.760099
title: Seal census raw data during campaign EMAGE-III
DOI: 10.1594/pangaea.760100
title: Seal census raw data during campaign EMAGE-IV
DOI: 10.1594/pangaea.760101
title: Seal census raw data during campaign EMAGE-V
DOI: 10.1594/pangaea.778263
title: Helicopter-borne sea ice thickness measurements during the POL-ICE field campaign in the Bay of Bothnia in March 2007 from flight HEM_POL-ICE07_01a
DOI: 10.1594/pangaea.778306
title: Helicopter-borne sea ice thickness measurements during the POL-ICE field campaign in the Bay of Bothnia in March 2007 from flight HEM_POL-ICE07_02a
DOI: 10.1594/pangaea.784104
title: Helicopter-borne sea ice thickness measurements during ARANDA campaign IRIS 2005 from flight HEM_IRIS05_04b
DOI: 10.1594/pangaea.784167
title: Helicopter-borne sea ice thickness measurements during campaign IRIS 2003 from flight HEM_IRIS03_08
DOI: 10.1594/pangaea.786877
title: Counts of fish species from trawl and dredge samples in the eastern Weddell Sea and at the Antarctic Peninsula during POLARSTERN cruise ANT-I/2

description: Depth, water is the mean sample depth.
DOI: 10.1594/pangaea.834009
title: Abundance of macrozoobenthos in surface sediments sampled during POLARSTERN cruise ANT-III/2

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.834013
title: Abundance of macrozoobenthos in surface sediments sampled during POLARSTERN cruise ANT-IX/3

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.834017
title: Abundance of macrozoobenthos in surface sediments sampled during POLARSTERN cruise ANT-VI/3

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.834025
title: Abundance of macrozoobenthos in surface sediments sampled during POLARSTERN cruise ANT-X/3

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.834029
title: Abundance of macrozoobenthos in surface sediments sampled during POLARSTERN cruise ANT-XIII/3

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.834065
title: Abundance of macrozoobenthos in surface sediments sampled during Walther Herwig II cruise WH068/2

description: Depth = penetration depth of gear (max = 45 cm).
DOI: 10.1594/pangaea.871025
title: Physical oceanography measured with CTD/Large volume Watersampler-system during POLARSTERN cruise PS100 (ARK-XXX/2)
DOI: 10.1594/pangaea.905443
title: Radionuclide 210Pb and 226Ra data measured on sediment cores during SONNE cruise SO242/1

description: Sediment profiles of 210Pb and 226Ra, radio-isotopes from the 234U decay series with half-lives of respectively 22.3 and 1600 year, were measured in multicores collected from the DISCOL Experimental Area in the Peru Basin during SO242-1, for determining biological mixing rates integrated over a ~100 year time-scale. Total 210Pb and 226Ra activity were determined directly by gamma-spectrometry, whilst total 210Pb was also measured indirectly by alpha-spectrometry via its granddaughter isotope 210Po. Activities of anthropogenic 137Cs proved to be generally below detection level. Radionuclide activities are reported in the data base as mBq g-1 dry sediment.For gamma-spectrometry measurement of 210Pb and 226Ra, 2-5 ml of freeze-dried and homogenized sediment was weighed and packed in a 6-cm diameter plastic Petri dish which then was sealed with electrical tape and packed in a sealed plastic envelope. Calibration and monitor standards and samples were prepared in the same geometry. Sealed sediment samples were left for a minimum of four weeks to establish radioactive equilibrium between 222Rn and 226Ra. Gamma activity was measured with a Canberra Broad Energy Range High Purity Germanium Detector (BEGe), using the 46.5 keV line for 210Pb and 295.2, 351.9 and 609.3 keV lines for 226Ra. The detector, connected to a computer via a Digital Spectrum Analyser (DSA-1000), counted the radionuclide activities with Genie 2000 gamma spectroscopy software. Samples were counted for 2–5 days to obtain good counting statistics or relative standard deviation (RSD). A blank (empty petri dish) was counted during 23 days. The detector was externally calibrated with a Geological Certified Reference Material IAEA/RGU-1, with reference date of 01-01-1988. A monitor standard IAEA-300 provided quality control. Excess 210Pb activities were calculated by subtracting 226Ra activity averaged for the 295.2, 351.9 and 609.3 keV lines from the measured total 210Pb activity.
DOI: 10.1594/wdcc/cbase
title: Using CALIOP to estimate cloud-field base height and its uncertainty: the Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm and dataset

description: Project: Cloudbase: satellite-derived cloud base heights - The Cloudbase project aims to provide datasets of satellite-derived cloud base heights and their uncertainties. Summary: Attenuated backscatter profiles from the CALIOP satellite lidar are used to estimate cloud base heights of lower-troposphere liquid clouds (cloud base height below approximately 3 km). Even when clouds are thick enough to attenuate the lidar beam (optical thickness &gt; 5), the technique provides cloud base heights by treating the cloud base height of nearby thinner clouds as representative of the surrounding cloud field. Using ground-based ceilometer data, uncertainty estimates for the cloud base height product at retrieval resolution are derived as a function of various properties of the CALIOP lidar profiles. Evaluation of the predicted cloud base heights and their predicted uncertainty using a second, statistically independent, ceilometer dataset shows that cloud base heights and uncertainties are biased by less than 10%. CBASE provides two files for each CALIOP VFM input file: one using a 40 km window to detect the cloud field base height, and one using a 100 km window. (The input CALIOP VFM dataset is organized by the daytime/nighttime half of each orbit.) The file name pattern is CBASE_T.nc (identical to the input CALIOP VFM file name with the exception of the product name). Files are organized into subdirectories by half-orbit start date.
DOI: 10.17026/dans-x3c-5cvq
title: Validation of SMAP L2 passive-only soil moisture products using in situ measurements collected in Twente, The Netherlands

description: This deposit includes the data used for the research presented in 'Validation of SMAP L2 passive-only soil moisture products using in situ measurements collected in Twente, The Netherlands' that will be submitted (d.d. September 5th, 2019) to the open access scientific journal Hydrology and Earth System Sciences (HESS). The data consists of:• In situ soil moisture and temperature measured from January 2015 till December 2018 at a soil depth of 5 cm by a network composed of twenty stations in the Twente region. The network of soil moisture stations is operated by the University of Twente.• Root zone soil moisture simulations for the Netherlands at 250 m resolution performed by the LHM (Landelijk Hydrologisch Model) maintained by Deltares.• NASA SMAP L2 passive-only soil moisture estimates (version R164020) for three reference pixels with different coverages of the Twente network.
DOI: 10.17632/5393ck97d9.3
title: Evaluation and optimization of snow albedo scheme in Noah-MP land surface model using in-situ spectral observations in the Colorado Rockies

description: This data records data used in the Abolafia-Rosenzweig et al. (2022) study. These data include BATS simulated ground snow albedo, in situ observed radiation and albedo from Rocky Mountain stations, in situ observed snow depth and Noah-MP in parameter tables. Data is described in detail in the README file.
DOI: 10.18140/flx/1440152
title: FLUXNET2015 DE-Tha Tharandt

description: This is the FLUXNET2015 version of the carbon flux data for the site DE-Tha Tharandt.
DOI: 10.18140/flx/1440178
title: FLUXNET2015 NL-Loo Loobos

description: This is the FLUXNET2015 version of the carbon flux data for the site NL-Loo Loobos.
DOI: 10.18140/flx/1440217
title: FLUXNET2015 DE-Seh Selhausen

description: This is the FLUXNET2015 version of the carbon flux data for the site DE-Seh Selhausen.
DOI: 10.18739/a2kg55
title: A synthesis dataset of near-surface permafrost conditions for Alaska, 1997-2016
DOI: 10.18751/climate/griddata/apgd/1.0
title: APGD: Alpine precipitation grid dataset

description: A spatial analysis of precipitation over the territory of the European Alps and adjacent flatland regions (4.8-17.5°E / 43-49°N, 47.6°N in France). The distribution of precipitation (rainfall plus snow water equivalent, in mm) is estimated for all days of the period 1971-2008. Estimates are based on measurements at high-resolution rain-gauge stations (more than 8500 in total) from meteorological and hydrological services. The analysis is provided on a regular grid in the ETRS89-LAEA coordinate system, with a grid spacing of 5x5 km. The high density of the observational input data contributes to quantitative accuracy  and high effective resolution (approx. 10-20 km) of precipitation estimates in the source region of available in Isotta et al. (2014). Created by Meteoswiss for the EURO4M project.
DOI: 10.18758/71021049
title: Ground-based FTIR CO2, CH4 and CO measurements at Xianghe, China

description: The data is generated during Yang Yang’s visiting PhD program at BIRA-IASB with the support from the China Scholarship Council. The Xianghe FTIR measurements are carried out under the collaboration between the Institute of Atmospheric Physics - Chinese Academy of Sciences (IAP-CAS) and Royal Belgian Institute for Space Aeronomy (BIRA-IASB). 

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