cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/0c17c247-8f79-4372-be4a-92d54223b143
title: AX_2 Fluorite database for MLFF training underlying the publication: Predictive accuracy of on-the-fly Machine Leaning Force Fields for superionic diffusion kinetics in AX_2 Fluorites

description: <strong>AX_2 fluorite database for force field training containing six materials: CaF2, Li2O, PbF2, SrCl2, SrF2, BaF2. </strong>The dataset has been used (and could be used by you) to train Machine Learning Force Fields (MLFFs) to simulate the (onset of) superionic phase.<br>These structures have been selected with the on-the-fly Machine-Learning Force Fields method (as implemented in VASP 6.3 and higher) and described in this reference:Jinnouchi R., Lahnsteiner J., Karsai F., Kresse G., Bokdam M., "Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on the fly with Bayesian inference", Phys. Rev. Lett. 122, 225701, (2019)<br>The structures have been automatically selected during a heating run from 800 to 2600 K and the corresponding coordinates, energies, forces and stresses are stored in the ML_AB file. The ML_AB file can be used to generate new force fields with the method of the users preference. The open-source FPdataViewer software can be used to read-in the ML_AB file. It also contains a connection to the Atomic Simulation Environment with which descriptors can be generated.<br><strong>Caution</strong>: There are 2 versions of the ML_AB databases included per fluorite:ML_AB_<strong>full</strong>: all data picked up by on-the-fly training, contains however ~20% molten structures with uncoverged DFT labels (ie. energies, forces, stress)ML_AB_<strong>filtered</strong>: a curated version of the data above, whereby all structures with lattice vectors deviating by more then 5% from the mean have been filtred out, cleaning up most of the unconverged labels. Files contain the *.out.* in the filename. <br><strong>FPdataviewer factsheets</strong>A high level overview of the ML_AB databases has been generated using the open-source FPdataViewer software (https://github.com/dynamicsolids/FPdataViewer). Each pdf file contains statistics related to the structures, energies and forces stored in the databases. The factsheet can be used to get a quick overview of the data stored in the database.
DOI: 10.60544/ch2h-qp85
title: Datasets and R code
DOI: 10.60544/ct3r-nx81
title: Datasets and R code
DOI: 10.15468/dl.s32vws
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.5688 22.04913, -108.4188 22.04913, -108.4188 22.19913, -108.5688 22.19913, -108.5688 22.04913))"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041142-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/0c17c247-8f79-4372-be4a-92d54223b143.v1
title: AX_2 Fluorite database for MLFF training underlying the publication: Predictive accuracy of on-the-fly Machine Leaning Force Fields for superionic diffusion kinetics in AX_2 Fluorites

description: <strong>AX_2 fluorite database for force field training containing six materials: CaF2, Li2O, PbF2, SrCl2, SrF2, BaF2. </strong>The dataset has been used (and could be used by you) to train Machine Learning Force Fields (MLFFs) to simulate the (onset of) superionic phase.<br>These structures have been selected with the on-the-fly Machine-Learning Force Fields method (as implemented in VASP 6.3 and higher) and described in this reference:Jinnouchi R., Lahnsteiner J., Karsai F., Kresse G., Bokdam M., "Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on the fly with Bayesian inference", Phys. Rev. Lett. 122, 225701, (2019)<br>The structures have been automatically selected during a heating run from 800 to 2600 K and the corresponding coordinates, energies, forces and stresses are stored in the ML_AB file. The ML_AB file can be used to generate new force fields with the method of the users preference. The open-source FPdataViewer software can be used to read-in the ML_AB file. It also contains a connection to the Atomic Simulation Environment with which descriptors can be generated.<br><strong>Caution</strong>: There are 2 versions of the ML_AB databases included per fluorite:ML_AB_<strong>full</strong>: all data picked up by on-the-fly training, contains however ~20% molten structures with uncoverged DFT labels (ie. energies, forces, stress)ML_AB_<strong>filtered</strong>: a curated version of the data above, whereby all structures with lattice vectors deviating by more then 5% from the mean have been filtred out, cleaning up most of the unconverged labels. Files contain the *.out.* in the filename. <br><strong>FPdataviewer factsheets</strong>A high level overview of the ML_AB databases has been generated using the open-source FPdataViewer software (https://github.com/dynamicsolids/FPdataViewer). Each pdf file contains statistics related to the structures, energies and forces stored in the databases. The factsheet can be used to get a quick overview of the data stored in the database.
DOI: 10.5517/ccdc.csd.cc2j0n9j
title: CCDC 2324327: Experimental Crystal Structure Determination

description: Related Article: wei-jie ji, Yue Wu, Ming-Hui Qi, Guo-Bin Ren|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.30483515.v13
title: Forvard step of Logic

description: Logic and more
DOI: 10.15468/dl.frqg8q
title: Occurrence Download

description: A dataset containing 142 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plecoptera",
 "Year 2000-2025"
 ]
}

 The dataset includes 142 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041147-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qbagpb
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Paraamphiope"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041145-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.82554/sdl-108.75
title: DT-GEO_SD4-samos

description: Input and output data related to DTC-T1 (i.e. Probabilistic Tsunami Forecasting, PTF) for the Site Demonstrator SD4 (the 2020 Samos-Izmir earthquake).
DOI: 10.15468/dl.va9tt5
title: Occurrence Download

description: A dataset containing 220 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronectes platessa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 1909"
 ]
}

 The dataset includes 220 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041146-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mfycjs
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Pedicularis ikomae",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041144-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.82554/sdl-110.77
title: DT-GEO_SD7-japan

description: Input and output data related to DTC-T1 (i.e. Probabilistic Tsunami Forecasting, PTF) for the Site Demonstrator SD7 (the 2011 Tohoku earthquake)
DOI: 10.15468/dl.fpwddm
title: Occurrence Download

description: A dataset containing 455 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Polystichum prescottianum",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 455 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041148-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g3yfjk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.4188 22.04913, -108.2688 22.04913, -108.2688 22.19913, -108.4188 22.19913, -108.4188 22.04913))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041149-251025141854904/datasets/export for details.
DOI: 10.25381/cput.30600632
title: A flexible service-learning model for Generation Z students at a university of technology

description: Service-learning (SL) is a well-established experiential pedagogy that enhances students' academic and personal development. However, the COVID-19 pandemic revealed significant challenges for traditional SL models, as restrictions limited opportunities for face-to-face interactions in the community. Drawing on generational theory, this paper centres on Generation Z (Gen Z) students at one university of technology, who are recognised for their digital fluency and a preference for flexible learning pathways. A mixed-methods design was adopted, involving purposive sampling of 43 Gen Z students and 7 SL lecturers at one higher education institution. Data were collected using semi-structured interviews, a focus group interview, and an online survey. The analysis revealed that Gen Z students are multimodal learners who favour varied learning pathways and do not possess a single dominant learning approach. Based on these findings, the paper presents a flexible service-learning model specifically developed to address the diverse learning preferences and characteristics of Gen Z students. The proposed model integrates advanced digital technologies to provide students with flexible learning approaches during SL projects and ensure continuity in the event of disruptions. This model aims to enhance the accessibility and resilience of SL experiences in both standard and crisis contexts, as well as align appropriately with the needs of Gen Z students.<br><br>
DOI: 10.25381/cput.30600632.v1
title: A flexible service-learning model for Generation Z students at a university of technology

description: Service-learning (SL) is a well-established experiential pedagogy that enhances students' academic and personal development. However, the COVID-19 pandemic revealed significant challenges for traditional SL models, as restrictions limited opportunities for face-to-face interactions in the community. Drawing on generational theory, this paper centres on Generation Z (Gen Z) students at one university of technology, who are recognised for their digital fluency and a preference for flexible learning pathways. A mixed-methods design was adopted, involving purposive sampling of 43 Gen Z students and 7 SL lecturers at one higher education institution. Data were collected using semi-structured interviews, a focus group interview, and an online survey. The analysis revealed that Gen Z students are multimodal learners who favour varied learning pathways and do not possess a single dominant learning approach. Based on these findings, the paper presents a flexible service-learning model specifically developed to address the diverse learning preferences and characteristics of Gen Z students. The proposed model integrates advanced digital technologies to provide students with flexible learning approaches during SL projects and ensure continuity in the event of disruptions. This model aims to enhance the accessibility and resilience of SL experiences in both standard and crisis contexts, as well as align appropriately with the needs of Gen Z students.<br><br>
DOI: 10.15468/dl.e6czwu
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronectes platessa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1910",
 "Year is less than or equal to 1919"
 ]
}

 The dataset includes 46 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041150-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zjs375
title: Occurrence Download

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Taxillus limprichtii",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 108 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041151-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mfdwgd
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.2688 22.04913, -108.1188 22.04913, -108.1188 22.19913, -108.2688 22.19913, -108.2688 22.04913))"
 ]
}

 The dataset includes 73 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041152-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5m52qm
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Angelica dahurica formosana",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 67 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041153-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/7023
title: class1
DOI: 10.15468/dl.x4jyz4
title: Occurrence Download

description: A dataset containing 478 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Festuca campestris",
 "HasCoordinate is true"
 ]
}

 The dataset includes 478 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041156-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fnxy6d
title: Occurrence Download

description: A dataset containing 233 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronectes platessa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1920",
 "Year is less than or equal to 1929"
 ]
}

 The dataset includes 233 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041158-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yuwd5q
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Parkia filicoidea",
 "Year 2015-2025"
 ]
}

 The dataset includes 48 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041155-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4akhkw
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Euphrasia transmorrisonensis durietziana",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 75 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041159-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v47xun
title: Occurrence Download

description: A dataset containing 16420 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((140.22922 -2.71380,140.74805 -2.71380,140.74805 -2.50636,140.22922 -2.50636,140.22922 -2.71380))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 16420 records from 115 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041157-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d47fqu
title: Occurrence Download

description: A dataset containing 605 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipodomys ingens"
 ]
}

 The dataset includes 605 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041160-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17637726
title: Microscale Native Size Exclusion Chromatography High Resolution Mass Spectrometry for the Determination of the Chelator-To-Antibody Ratio of Immunoconjugates

description: Raw SEC-MS data of the following immunoconjugates: trastuzumab-N-suc-DFO, trastuzumab-mal-DFO, trastuzumab-TMTHSI-DFO, trastuzumab-NCS-DFO and ipilimumab-N-suc-DFO. Also included here are the tested buffer concentrations (200–1000 mM ammonium acetate) of trastuzumab-N-suc-DFO.
DOI: 10.5281/zenodo.17637725
title: Microscale Native Size Exclusion Chromatography High Resolution Mass Spectrometry for the Determination of the Chelator-To-Antibody Ratio of Immunoconjugates

description: Raw SEC-MS data of the following immunoconjugates: trastuzumab-N-suc-DFO, trastuzumab-mal-DFO, trastuzumab-TMTHSI-DFO, trastuzumab-NCS-DFO and ipilimumab-N-suc-DFO. Also included here are the tested buffer concentrations (200–1000 mM ammonium acetate) of trastuzumab-N-suc-DFO.
DOI: 10.5281/zenodo.17637480
title: Uncertainties in research papers

description: Research papers are usually seen as the strongest and most trustworthy source of knowledge, but they still carry a lot of uncertainty behind them. This uncertainty doesn’t always come from errors. Sometimes it’s because the study was done on a small group of people, or the methods were not explained clearly, or the results were pushed out quickly because of pressure to publish. Even the peer review process, which people assume is a perfect filter, depends on a few reviewers who are limited by time and their own understanding. So it doesn’t always catch everything.

This review looks at the common reasons behind these uncertainties and how they shape the final claims a paper makes. It also talks about why many studies fail when someone tries to repeat them, and what small signs in a paper like missing details, selective reporting, or results that look perfect can tell us about the reliability of the work. The purpose is not to judge researchers but to give a clearer picture of how scientific papers actually come to life. When readers understand both the strength and the limits of research, they can read papers with better awareness and judge what they truly prove, and where more careful checking is needed.
DOI: 10.5281/zenodo.17637479
title: Uncertainties in research papers

description: Research papers are usually seen as the strongest and most trustworthy source of knowledge, but they still carry a lot of uncertainty behind them. This uncertainty doesn’t always come from errors. Sometimes it’s because the study was done on a small group of people, or the methods were not explained clearly, or the results were pushed out quickly because of pressure to publish. Even the peer review process, which people assume is a perfect filter, depends on a few reviewers who are limited by time and their own understanding. So it doesn’t always catch everything.

This review looks at the common reasons behind these uncertainties and how they shape the final claims a paper makes. It also talks about why many studies fail when someone tries to repeat them, and what small signs in a paper like missing details, selective reporting, or results that look perfect can tell us about the reliability of the work. The purpose is not to judge researchers but to give a clearer picture of how scientific papers actually come to life. When readers understand both the strength and the limits of research, they can read papers with better awareness and judge what they truly prove, and where more careful checking is needed.
DOI: 10.15468/dl.92tetx
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.1188 22.04913, -107.9688 22.04913, -107.9688 22.19913, -108.1188 22.19913, -108.1188 22.04913))"
 ]
}

 The dataset includes 13 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041161-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xzkttd
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "AcceptedTaxonKey is Salix morrisonicola",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 30 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041163-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uvc74d
title: Occurrence Download

description: A dataset containing 853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "TaxonKey is Lycaon pictus"
 ]
}

 The dataset includes 853 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041164-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.