cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.tyed77
title: Occurrence Download

description: A dataset containing 906 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Limonium duriusculum"
 ]
}

 The dataset includes 906 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044988-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.69kg85
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nereis granulata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044989-251120083545085/datasets/export for details.
DOI: 10.15468/dl.ggm2wj
title: Occurrence Download

description: A dataset containing 138277 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alces alces",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 138277 records from 162 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044907-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2t8wcq
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((105.187 -4.643848, 105.116507 -4.649411, 105.047746 -4.665963, 104.982407 -4.693098, 104.922097 -4.730149, 104.8683 -4.776204, 104.822339 -4.830131, 104.785346 -4.890604, 104.758234 -4.956136, 104.741672 -5.025115, 104.736072 -5.095842, 104.741575 -5.166577, 104.758048 -5.235577, 104.785091 -5.301143, 104.822039 -5.36166, 104.867985 -5.415635, 104.921798 -5.461738, 104.982152 -5.498832, 105.04756 -5.526001, 105.116409 -5.542575, 105.187 -5.548146, 105.257591 -5.542575, 105.32644 -5.526001, 105.391848 -5.498832, 105.452202 -5.461738, 105.506015 -5.415635, 105.551961 -5.36166, 105.588909 -5.301143, 105.615952 -5.235577, 105.632425 -5.166577, 105.637928 -5.095842, 105.632328 -5.025115, 105.615766 -4.956136, 105.588654 -4.890604, 105.551661 -4.830131, 105.5057 -4.776204, 105.451903 -4.730149, 105.391593 -4.693098, 105.326254 -4.665963, 105.257493 -4.649411, 105.187 -4.643848))"},{"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 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044990-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/qu3t65
title: ARMS-MBON data on long-term monitoring of hard-bottom communities: 18S results from 2020-2021

description: &lt;p&gt;ARMS-MBON is a network of more than 25 partners who deploy Autonomous Reef Monitoring Structures (ARMS) settlement units in the vicinity of marine stations and Long-term Ecological Research sites in European coastal waters and Ant/arctica. After a few months the units are brought up, and visual, photographic, and genetic assessments are made of the lifeforms that settled on them. The collected data are published (see the related datasets and GitHub links listed in this record) and the omics data analysed. &lt;/p&gt;&lt;p&gt;In this record we include the outputs of our analysis of the 18S data from the 2020-2022 campaign. The analysis used the PEMA bioinformatics software, and the resulting taxonomics inventory has been turned into DwC format. In addition, all the PEMA inputs and outputs can be found on the ARMS-MBON GitHub site (see links in this record), and the subset of the sampling data to which these 18S results are linked can also be found on the ARMS-MBON GitHub site.&lt;/p&gt;
DOI: 10.15468/dl.9dmrx4
title: Occurrence Download

description: A dataset containing 360 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudonereis variegata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 360 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044992-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13130/rd_unimi/nncxqa
title: 01 - Radar Precipitation extraction 2005 - 2020

description: Hourly precipitation values extracted from raster related to MeteoSWISS radar outputs. The values represent the average, minimum and maximum hourly precipitation in the cell (1km X 1km) corresponding to the ARPA station of Grosio. After extracting the data from the raster cell corresponding to the weather station (values from 0 to 255), they are reclassified according to a conversion table whose result is the mean value, minimum and maximum expressed in mm/h. 
Naming conventions:
for the extraction:
combPointValue_yyyy.csv
for example, combPointValue_2005.csv
for the conversion:
Type_Value_intensity.csv
for example, Stations_Value_min.csv or Centroids_Value_min.csv
description: These data have been generated during PhD project "Modelling current and future water resources availability in an Alpine catchment exploited for hydropower production" - XXXVI cycle 2020-2024 - PhD Thesis Chapter 4
description: RStudio
description: Microsoft Excel
description: arcGIS, 10.5
DOI: 10.13130/rd_unimi/nncxqa/lvt16k
title: combPointValue_2007.csv
DOI: 10.13130/rd_unimi/nncxqa/ul9b0c
title: combPointValue_2018.csv
DOI: 10.13130/rd_unimi/nncxqa/vmwxgb
title: combPointValue_2014.csv
DOI: 10.13130/rd_unimi/nncxqa/4cndbo
title: combPointValue_2010.csv
DOI: 10.34740/kaggle/dsv/14093429
title: BOS Kemdikbud
DOI: 10.13130/rd_unimi/nncxqa/gkunxe
title: combPointValue_2011.csv
DOI: 10.13130/rd_unimi/nncxqa/wnl3lw
title: combPointValue_2013.csv
DOI: 10.13130/rd_unimi/nncxqa/efd423
title: combPointValue_2012.csv
DOI: 10.13130/rd_unimi/nncxqa/ojnafw
title: Stations_Value_min.tab
DOI: 10.13130/rd_unimi/nncxqa/ehjeuo
title: combPointValue_2009.csv
DOI: 10.13130/rd_unimi/nncxqa/92p1mu
title: combPointValue_2017.csv
DOI: 10.13130/rd_unimi/nncxqa/n0rzur
title: Centroids_Value_mean.tab
DOI: 10.13130/rd_unimi/nncxqa/yjzxos
title: combPointValue_2019.csv
DOI: 10.13130/rd_unimi/nncxqa/kl5cif
title: combPointValue_2015.csv
DOI: 10.13130/rd_unimi/nncxqa/uylqgy
title: Centroids_Value_max.tab
DOI: 10.13130/rd_unimi/nncxqa/qpxgqp
title: combPointValue_2005.csv
DOI: 10.13130/rd_unimi/nncxqa/bbtena
title: Stations_Value_max.tab
DOI: 10.13130/rd_unimi/nncxqa/2llbup
title: combPointValue_2016.csv
DOI: 10.13130/rd_unimi/nncxqa/i6rhkt
title: Centroids_Value_min.tab
DOI: 10.13130/rd_unimi/nncxqa/jqv5yt
title: combPointValue_2006.csv
DOI: 10.13130/rd_unimi/nncxqa/lq4qx5
title: Stations_Value_mean.tab
DOI: 10.13130/rd_unimi/nncxqa/ie520q
title: combPointValue_2020.csv
DOI: 10.13130/rd_unimi/nncxqa/fpcu3u
title: combPointValue_2008.csv
DOI: 10.13130/rd_unimi/nncxqa/vyxctu
title: README.txt

description: READ ME
DOI: 10.15468/7dzrn7
title: eDNA-based Assessment of Marine Vertebrate Diversity in Svalbard Coastal Waters

description: This dataset contains the data from an environmental DNA metabarcoding sampling campaign conducted on the west coast of Svalbard in June 2025 to investigate marine vertebrate biodiversity.
[This dataset was processed using the GBIF Metabarcoding Data Toolkit.]
DOI: 10.15468/dl.8qfygm
title: Occurrence Download

description: A dataset containing 2895 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-0.90287 53.45471,0.20302 53.45471,0.20302 53.92852,-0.90287 53.92852,-0.90287 53.45471))",
 "HasGeospatialIssue is false",
 "TaxonKey is Tyto alba"
 ]
}

 The dataset includes 2895 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044994-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3y9trn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((151.225 -4.641848, 151.154507 -4.647411, 151.085746 -4.663963, 151.020408 -4.691098, 150.960098 -4.728149, 150.906301 -4.774204, 150.86034 -4.828131, 150.823347 -4.888604, 150.796235 -4.954136, 150.779673 -5.023115, 150.774073 -5.093842, 150.779576 -5.164577, 150.79605 -5.233577, 150.823092 -5.299144, 150.86004 -5.35966, 150.905986 -5.413635, 150.959798 -5.459738, 151.020153 -5.496832, 151.085561 -5.524001, 151.154409 -5.540575, 151.225 -5.546146, 151.295591 -5.540575, 151.364439 -5.524001, 151.429847 -5.496832, 151.490202 -5.459738, 151.544014 -5.413635, 151.58996 -5.35966, 151.626908 -5.299144, 151.65395 -5.233577, 151.670424 -5.164577, 151.675927 -5.093842, 151.670327 -5.023115, 151.653765 -4.954136, 151.626653 -4.888604, 151.58966 -4.828131, 151.543699 -4.774204, 151.489902 -4.728149, 151.429592 -4.691098, 151.364254 -4.663963, 151.295493 -4.647411, 151.225 -4.641848))"},{"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/0044995-251120083545085/datasets/export for details.
DOI: 10.15468/j8bhdx
title: DFO Monthly GRDI Survey eDNA metabarcoding (COI) in Halifax 2021-2022

description: Environmental DNA (eDNA) is a non-invasive monitoring approach increasingly used to detect marine organisms; however, misunderstandings of the temporal variability in eDNA detection has limited its integration within management decisions. A clearer understanding of the periodicity (e.g., seasonality) and duration (e.g., weeks, months) of species eDNA detection is essential to optimize sampling design and data interpretation. As such, this study aims to provide a representative assessment of optimal eDNA detection windows across diverse taxonomic groups, primers, and geographic regions using eDNA metabarcoding. Coastal marine presence-absence eDNA data were collected along the Northwest Atlantic coast, in the Bay of Fundy, Scotian Shelf, and Baffin Island. eDNA detection window(s) were defined as unimodal, contiguous months having greater than 75% detection probability and were calculated for each taxon for each primer in each region. Most marine species exhibited short eDNA detection windows (1–2 months). The optimal sampling periods and durations were conserved among closely related species, highlighting the importance of considering biological traits when designing and interpreting eDNA studies. Additionally, primer choice influenced the optimal detection periods, with higher seasonal variation in community composition and detection rates using universal COI and 18S primers compared to fish 16S and 12S primers. These results demonstrate that ignoring seasonal variation may cause false negatives, inefficient sampling, and reduced data comparability across independent studies, emphasizing the need for temporal considerations when designing eDNA studies. Thus, we propose a set of guidelines aimed at the development of optimal sampling designs for coastal ecosystems and the interpretation of trends across datasets. This dataset is for the COI mitochondrial gene in Halifax. DNA derived data from the Bay of Fundy and Iqaluit are also available in OBIS.
DOI: 10.21227/0ssk-8c26
title: "Sistema De Detecci\u00f3n Temprana De Indicadores De Autismo Mediante Procesamiento De Im\u00e1genes y Roboflow"

description: "Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication difficulties, repetitive behaviors, and atypical visual attention patterns. Early identification of ASD is essential to improving therapeutic intervention and long-term developmental outcomes. However, traditional evaluation methods rely heavily on clinical observations and specialist-administered questionnaires, often delaying diagnosis, particularly in areas with limited professional services. In this context, digital image processing and machine learning have emerged as promising tools to support diagnostic processes.This article proposes a computer vision\u2013based system that uses Roboflow for dataset management, annotation, and model training aimed at detecting visual indicators associated with early ASD traits, such as reduced eye contact, limited facial emotional response, and atypical body orientation. A standardized dataset containing ethically authorized images was created and processed through augmentation, normalization, and segmentation techniques to enhance model robustness. Training was performed using YOLOv8-based architectures optimized for real-time detection, complemented by a structured clinical questionnaire to increase classification accuracy Preliminary results show an accuracy above 85.4% in detecting relevant facial features, with stable performance across varied lighting conditions and mobile devices. These findings demonstrate the potential of combining computer vision with contextual information to support early ASD screening."
DOI: 10.5281/zenodo.15366461
title: IODP Expedition 400 Alkalinity and pH

description: Alkalinity was determined by Gran titration with an autotitrator (Metrohm 794 basic Titrino) using 0.1 M HCl at 20 degrees C. Report includes alkalinity, correction factor (if applicable), and pH.
DOI: 10.5281/zenodo.15366462
title: IODP Expedition 400 Alkalinity and pH

description: Alkalinity was determined by Gran titration with an autotitrator (Metrohm 794 basic Titrino) using 0.1 M HCl at 20 degrees C. Report includes alkalinity, correction factor (if applicable), and pH.
DOI: 10.5281/zenodo.17881339
title: ebrejonl/Boletus_fruiting_triggers: Initial submission

description: Initial submission for the manuscript: Predicting porcini: a decade of sporocarp monitoring reveals the meteorological triggers of Boletus edulis fruiting in central European beech forests.
DOI: 10.5281/zenodo.17881359
title: ebrejonl/Boletus_fruiting_triggers: Initial submission

description: Initial submission for the manuscript: Predicting porcini: a decade of sporocarp monitoring reveals the meteorological triggers of Boletus edulis fruiting in central European beech forests.
DOI: 10.15468/4ppy93
title: ARMS-MBON data on long-term monitoring of hard-bottom communities: ITS results from 2020-2021

description: &lt;p&gt;ARMS-MBON is a network of more than 25 partners who deploy Autonomous Reef Monitoring Structures (ARMS) settlement units in the vicinity of marine stations and Long-term Ecological Research sites in European coastal waters and Ant/arctica. After a few months the units are brought up, and visual, photographic, and genetic assessments are made of the lifeforms that settled on them. The collected data are published (see the related datasets and GitHub links listed in this record) and the omics data analysed. &lt;/p&gt;&lt;p&gt;In this record we include the outputs of our analysis of the ITS data from the 2020-2022 campaign. The analysis used the PEMA bioinformatics software, and the resulting taxonomics inventory has been turned into DwC format. In addition, all the PEMA inputs and outputs can be found on the ARMS-MBON GitHub site (see links in this record), and the subset of the sampling data to which these 18S results are linked can also be found on the ARMS-MBON GitHub site.&lt;/p&gt;
DOI: 10.5167/uzh-280893
title: Max Zeltner
DOI: 10.5281/zenodo.15366528
title: IODP Expedition 400 Carbonates composite report

description: This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the  CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
DOI: 10.5281/zenodo.15366529
title: IODP Expedition 400 Carbonates composite report

description: This composite report includes data from two analyses (total carbon from Elemental analysis [CHNS], and inorganic carbon from [Coulometer]). Each row combines the  CHNS and Coulometer data from measurements made on the same sample at the same time for a particular section and section offset (depth). If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate data type (Elemental analysis and Coulometer). If the same sample was measured multiple times by any of the methods, results in the report will be combined on one line where possible. Each additional replicate result will be shown in subsequent rows and will be combined where possible. Report includes results for carbon forms: total, inorganic, calcium carbonate, and organic by difference, along with total hydrogen, nitrogen, and sulfur.
DOI: 10.15468/dl.cbjzp2
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudonereis gallapagensis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 121 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044998-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15366530
title: IODP Expedition 400 Elemental analysis (CHNS)

description: Fundamental elemental component (total carbon, hydrogen, nitrogen, and sulfur) fluctuations help define the origin, depositional environment, and diagenetic alteration of source materials. To determine C, H, N, and S, solid samples are reacted with a catalyst, separated by chromatography, and detected by thermal conductivity on a FlashEA 1112 CHNS elemental analyzer. Organic carbon can be directly measured on the elemental analyzer by acidification of the sample to drive off carbonate as carbon dioxide before analyzing. Total organic carbon on this report is measured rather than calculated.
DOI: 10.5281/zenodo.15366531
title: IODP Expedition 400 Elemental analysis (CHNS)

description: Fundamental elemental component (total carbon, hydrogen, nitrogen, and sulfur) fluctuations help define the origin, depositional environment, and diagenetic alteration of source materials. To determine C, H, N, and S, solid samples are reacted with a catalyst, separated by chromatography, and detected by thermal conductivity on a FlashEA 1112 CHNS elemental analyzer. Organic carbon can be directly measured on the elemental analyzer by acidification of the sample to drive off carbonate as carbon dioxide before analyzing. Total organic carbon on this report is measured rather than calculated.
DOI: 10.13130/rd_unimi/cz8ioh
title: 09 - Kriging OK and DK correction

description: Spatial Kriging OK and DK correction of the hourly radar precipitation values for each centroid of the study area.
Once the residuals at the rain gauge locations were calculated with respect to the radar, the error was interpolated exploiting the Ordinary (OK) and Detrended (DK) kriging techniques and added to the radar values in each 1 km x 1 km cell (radar considered as the trend).
Naming conventions:
P_R_kr_ord_n°.csv and P_R_kr_det_n°.csv
for example, P_R_kr_ord_2.csv, number varies based on the centroid which it refers to.
description: These data have been generated during PhD project "Modelling current and future water resources availability in an Alpine catchment exploited for hydropower production" - XXXVI cycle 2020-2024 - PhD Thesis Chapter 4
description: RStudio
DOI: 10.13130/rd_unimi/cz8ioh/2v6m3b
title: P_R_kr_det_37.csv
DOI: 10.13130/rd_unimi/cz8ioh/iwyqcq
title: P_R_kr_ord_14.csv
DOI: 10.5167/uzh-281223
title: Carmen Martin Gaite, “La conciencia tranquila”; “Un alto en el camino” [“The Quiet Conscience”; “A Stop Along the Way”]
DOI: 10.13130/rd_unimi/cz8ioh/9wg6e5
title: P_R_kr_det_25.csv
DOI: 10.13130/rd_unimi/cz8ioh/xicv8x
title: P_R_kr_det_29.csv
DOI: 10.5281/zenodo.15366532
title: IODP Expedition 400 Closeup images

description: Close-up images taken by digital cameras as requested by the science party, typically when the section-half image is not sufficient. Close-up photographs of the areas of interest may be taken from whole-round sections, pieces, or section halves in sediments and rock.
DOI: 10.5281/zenodo.15366533
title: IODP Expedition 400 Closeup images

description: Close-up images taken by digital cameras as requested by the science party, typically when the section-half image is not sufficient. Close-up photographs of the areas of interest may be taken from whole-round sections, pieces, or section halves in sediments and rock.
DOI: 10.13130/rd_unimi/cz8ioh/anb3al
title: P_R_kr_det_12.csv
DOI: 10.15468/j48gxb
title: eDNA-based biodiversity monitoring in the Grand Port Maritime de Guadeloupe

description: This dataset includes occurrences of marine vertebrates recorded at four sites in the Grand Port Maritime of Guadeloupe (French Caribbean) in December 2023.[This dataset was processed using the GBIF Metabarcoding Data Toolkit.]
DOI: 10.13130/rd_unimi/cz8ioh/bzqet3
title: P_R_kr_ord_24.csv
DOI: 10.13130/rd_unimi/cz8ioh/kp7ezl
title: P_R_kr_ord_9.csv
DOI: 10.13130/rd_unimi/cz8ioh/obl6xf
title: P_R_kr_det_43.csv
DOI: 10.13130/rd_unimi/cz8ioh/yp4mg9
title: P_R_kr_det_24.csv
DOI: 10.13130/rd_unimi/cz8ioh/8aeyeb
title: P_R_kr_ord_2.csv
DOI: 10.13130/rd_unimi/cz8ioh/necqzy
title: P_R_kr_det_33.csv
DOI: 10.15468/dl.tvpfcn
title: Occurrence Download

description: A dataset containing 682130 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Local floras of Russia: records from literature"
 ]
}

 The dataset includes 682130 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044984-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13130/rd_unimi/cz8ioh/y6uzfx
title: P_R_kr_det_17.csv
DOI: 10.13130/rd_unimi/cz8ioh/wtmazy
title: P_R_kr_det_35.csv
DOI: 10.13130/rd_unimi/cz8ioh/nxoypy
title: P_R_kr_ord_10.csv
DOI: 10.13130/rd_unimi/cz8ioh/kzhpao
title: P_R_kr_ord_30.csv
DOI: 10.13130/rd_unimi/cz8ioh/wjjeig
title: P_R_kr_det_45.csv
DOI: 10.13130/rd_unimi/cz8ioh/83u77g
title: P_R_kr_ord_21.csv
DOI: 10.13130/rd_unimi/cz8ioh/mxirka
title: P_R_kr_ord_39.csv
DOI: 10.13130/rd_unimi/cz8ioh/ntklgu
title: P_R_kr_det_8.csv