cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17188/1722077
title: Materials Data on V2ReRh by Materials Project

description: V2ReRh crystallizes in the orthorhombic Immm space group. The structure is one-dimensional and consists of two V2ReRh ribbons oriented in the (1, 0, 0) direction. V is bonded in a linear geometry to one Re and one Rh atom. The V–Re bond length is 2.26 Å. The V–Rh bond length is 2.26 Å. Re is bonded in a linear geometry to two equivalent V atoms. Rh is bonded in a linear geometry to two equivalent V atoms.
DOI: 10.17188/1722078
title: Materials Data on Li2CuAg by Materials Project

description: Li2AgCu crystallizes in the orthorhombic Immm space group. The structure is one-dimensional and consists of two Li2AgCu ribbons oriented in the (1, 0, 0) direction. Li is bonded in a linear geometry to one Ag and one Cu atom. The Li–Ag bond length is 2.56 Å. The Li–Cu bond length is 2.43 Å. Ag is bonded in a linear geometry to two equivalent Li atoms. Cu is bonded in a linear geometry to two equivalent Li atoms.
DOI: 10.5281/zenodo.7893942
title: Asphalt profile temperatures and weather data of CyPaTs test track

description: This dataset includes asphalt temperature measurements and weather data of CyPaTs test track located at Campus Groenenborger, University of Antwerp, Antwerp, Belgium. The recorded asphalt temperature measurements and weather data is between March 17<sup>th</sup>, 2021, and March 14<sup>th</sup>, 2022. There are five sheets in each excel file, containing asphalt temperatures at various depths (near-surface, 4cm, 7cm and 10 below asphalt surface), and corresponding weather data. The total number of data points is 371707, with each of these data points including information on weather parameters and 45 sensors embedded in different layers of the asphalt pavement. Date (time): time of the recorded data TC_x-x: label of the temperature sensor embedded in asphalt pavement, in °C Ta: ambient air temperature, in °C RH: relative humidity, in % FF: wind speed, in m/s SR: solar radiation, in W/m<sup>2</sup>
DOI: 10.5281/zenodo.7895245
title: Asphalt profile temperatures and weather data of CyPaTs test track

description: This dataset includes asphalt temperature measurements and weather data of CyPaTs test track located at Campus Groenenborger, University of Antwerp, Antwerp, Belgium. The recorded asphalt temperature measurements and weather data is between March 17<sup>th</sup>, 2021, and March 14<sup>th</sup>, 2022. There are five sheets in each excel file, containing asphalt temperatures at various depths (near-surface, 4cm, 7cm and 10 below asphalt surface), and corresponding weather data. The total number of data points is 371707, with each of these data points including information on weather parameters and 45 sensors embedded in different layers of the asphalt pavement. Date (time): time of the recorded data TC_x-x: label of the temperature sensor embedded in asphalt pavement, in °C Ta: ambient air temperature, in °C RH: relative humidity, in % FF: wind speed, in m/s SR: solar radiation, in W/m<sup>2</sup>
DOI: 10.6084/m9.figshare.22758569
title: Unexpected deposition by rainfall of globally transportable microplastics (&lt;25 μm) hovering over the megacity of Beijing

description: Microplastics of &lt;25 μm have been identified as possessing globally transportable features, but the impact of precipitation on their transport remains unclear. Here, microplastics were detected in all ten rainfall events in the megacity of Beijing, with &lt;25 μm microplastics present in eight rainfalls. Interestingly, microplastic abundance was tentatively linked to maximum rainfall intensity, ranging from 7590 to 136778 items·m‒3, with &lt;25 μm microplastics making up 39.6(±27.5)% of the total count. The shapes of microplastics were fragments, fibers, and films. The composition of &lt;25 μm microplastics significantly differed from the larger microplastics, although both mainly comprised polystyrene, polyethylene, and polypyrene. Distinct differences were noted for the microplastic communities among different rainfalls, suggesting atmospheric transport is a highly dynamic process. The deposited microplastics were unstable and highly fragmented according to the conditional fragmentation model. The microplastic deposition rate was calculated as 2‒463 μg·m‒2·d‒1 (146–8629 items·m‒2·d‒1), amounting to 76.31 tons annually in Beijing. Although &lt;25 μm microplastics represented a negligible proportion (0.00‒1.24%) of the overall mass load of microplastics, their numerical abundance was high. Our results demonstrate precipitation is an effective mechanism for removing airborne microplastics, which may enter urban soils and waters and exacerbate microplastic burdens in the urban environment.
DOI: 10.5281/zenodo.7895259
title: my data trials for bci with different name

description: Changing the names of the files to try changing less of the original code.
DOI: 10.5281/zenodo.7895258
title: my data trials for bci with different name

description: Changing the names of the files to try changing less of the original code.
DOI: 10.5517/ccdc.csd.cc2fb251
title: CCDC 2244002: Experimental Crystal Structure Determination

description: Related Article: Jack Emerson-King, Adrian B. Chaplin|2023|Dalton Trans.|52|5044|doi:10.1039/D3DT00567D
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: 10.5517/ccdc.csd.cc2fb262
title: CCDC 2244003: Experimental Crystal Structure Determination

description: Related Article: Jack Emerson-King, Adrian B. Chaplin|2023|Dalton Trans.|52|5044|doi:10.1039/D3DT00567D
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: 10.5281/zenodo.7745713
title: RealCMB

description: The RealCMB dataset comprises 58 sets of images, each containing blurry, sharp, and depth images, as well as synchronized RGB frames, poses, and depth maps. Out of the 58 sets, 48 were recorded using the data collection app from Chugovov et al. 2022, while the remaining 10 sets were already available in Chugovov et al. 2022. If you use it, please cite: <pre><code>@inproceedings{torres2023parallaxicb, title={Depth-Aware Image Compositing Model for Parallax Camera Motion Blur}, author={Torres, German F and K{\"a}m{\"a}r{\"a}inen, Joni}, booktitle={Image Analysis: 23rd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18--21, 2023, Proceedings, Part I}, pages={279--296}, year={2023}, organization={Springer} }</code></pre>
DOI: 10.5281/zenodo.7745712
title: RealCMB

description: The RealCMB dataset comprises 58 sets of images, each containing blurry, sharp, and depth images, as well as synchronized RGB frames, poses, and depth maps. Out of the 58 sets, 48 were recorded using the data collection app from Chugovov et al. 2022, while the remaining 10 sets were already available in Chugovov et al. 2022. If you use it, please cite: <pre><code>@inproceedings{torres2023parallaxicb, title={Depth-Aware Image Compositing Model for Parallax Camera Motion Blur}, author={Torres, German F and K{\"a}m{\"a}r{\"a}inen, Joni}, booktitle={Image Analysis: 23rd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18--21, 2023, Proceedings, Part I}, pages={279--296}, year={2023}, organization={Springer} }</code></pre>
DOI: 10.5281/zenodo.7746117
title: VirtualCMB

description: The VirtualCMB dataset comprises 983 synthetic blurred images, accompanied by their corresponding latent sharp images, depth maps, and camera motion. The images and depth maps are rendered through the Unity engine using five different high-quality 3D scenes, which are readily available in the Unity asset store. If you use it, please cite: <pre><code>@inproceedings{torres2023parallaxicb, title={Depth-Aware Image Compositing Model for Parallax Camera Motion Blur}, author={Torres, German F and K{\"a}m{\"a}r{\"a}inen, Joni}, booktitle={Image Analysis: 23rd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18--21, 2023, Proceedings, Part I}, pages={279--296}, year={2023}, organization={Springer} }</code></pre>
DOI: 10.5281/zenodo.7746116
title: VirtualCMB

description: The VirtualCMB dataset comprises 983 synthetic blurred images, accompanied by their corresponding latent sharp images, depth maps, and camera motion. The images and depth maps are rendered through the Unity engine using five different high-quality 3D scenes, which are readily available in the Unity asset store. If you use it, please cite: <pre><code>@inproceedings{torres2023parallaxicb, title={Depth-Aware Image Compositing Model for Parallax Camera Motion Blur}, author={Torres, German F and K{\"a}m{\"a}r{\"a}inen, Joni}, booktitle={Image Analysis: 23rd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18--21, 2023, Proceedings, Part I}, pages={279--296}, year={2023}, organization={Springer} }</code></pre>
DOI: 10.35003/jeno4t
title: Replication Data for: Formation of Thermochemical Heterogeneities by Core-Mantle Interaction

description: The core-mantle boundary (CMB) shows a complex structure. Seismologists have observed features that are possibly denser than their surroundings. These structures form from a dense layer above the CMB. Therefore typical mantle convection models have assumed an initial dense basal layer. The thickness and density of this prescribed layer are crucial but hardly constrained. Here we investigate core-mantle interaction as one possible origin for this layer and employ 2D Cartesian models of mantle convection that consider a diffusive chemical gradient between the iron-rich core and the silicate mantle. Our simulations show that the diffusive influx is coupled to the convective mantle flow. Convection-assisted diffusion gives a larger influx beneath slabs spreading over the CMB. Additionally, as in the models with a prescribed layer, the rising plumes pull dense material up and form piles. In this study, however, the constant chemical influx leads to piles existing for longer times. The piles are typically smaller but can maybe in combination with a primordial layer explain different seismologically observed structures and the presence of core material in the mantle.
DOI: 10.35003/jeno4t/3vmhro
title: table-Figure4-B1.2.dat

description: :unav
DOI: 10.35003/jeno4t/fiqv8y
title: table-Figure6b-Volume-Ra2e4.dat

description: :unav
DOI: 10.35003/jeno4t/kcql5z
title: table-Figure6a-Volume-Le100.dat

description: :unav
DOI: 10.35003/jeno4t/z6cnlh
title: table-Figure2b-time0.0039.dat

description: :unav
DOI: 10.35003/jeno4t/fzbszs
title: table-Figure6d-Volume-H1C.dat

description: :unav
DOI: 10.35003/jeno4t/rou7wl
title: table-Figure6b-Height-Ra1e4.dat

description: :unav
DOI: 10.35003/jeno4t/ctq9be
title: table-Figure7a-time0.00228.dat

description: :unav
DOI: 10.35003/jeno4t/gycurz
title: table-Figure6c-Height-B2.dat

description: :unav
DOI: 10.35003/jeno4t/d1c12j
title: table-Figure5b-noflux15.dat

description: :unav
DOI: 10.35003/jeno4t/hegpia
title: table-Figure6c-Volume-B0.6.dat

description: :unav
DOI: 10.35003/jeno4t/1iance
title: table-Figure4g.dat

description: :unav
DOI: 10.35003/jeno4t/ai7obn
title: table-Figure6c-Volume-B1.2.dat

description: :unav
DOI: 10.35003/jeno4t/d7svix
title: table-Figure6a-Height-Le100.dat

description: :unav
DOI: 10.35003/jeno4t/rmprnr
title: table-Figure5a.dat

description: :unav
DOI: 10.35003/jeno4t/6itgyc
title: table-Figure6c-Height-B2.5.dat

description: :unav
DOI: 10.35003/jeno4t/9ar4pb
title: table-Figure2b-time0.131.dat

description: :unav
DOI: 10.35003/jeno4t/ouhris
title: table-Figure6d-Height-H1.dat

description: :unav
DOI: 10.35003/jeno4t/2wwhbz
title: table-Figure6b-Height-Ra1e3.dat

description: :unav
DOI: 10.35003/jeno4t/wvcyyi
title: table-Figure7b-time0.00228.dat

description: :unav
DOI: 10.35003/jeno4t/ysxbkw
title: table-Figure6c-Volume-B5.dat

description: :unav
DOI: 10.35003/jeno4t/mze0ew
title: table-Figure2b-time0.0011.dat

description: :unav
DOI: 10.35003/jeno4t/qpty8x
title: table-Figure2a-time0.131.dat

description: :unav
DOI: 10.35003/jeno4t/rzh9ed
title: table-Figure4-Le10.dat

description: :unav
DOI: 10.35003/jeno4t/pv53xa
title: table-Figure2b-time0.0.dat

description: :unav
DOI: 10.35003/jeno4t/niyg96
title: table-Figure6b-Volume-Ra1e3.dat

description: :unav
DOI: 10.35003/jeno4t/9q7ptn
title: table-Figure6d-Height-H1C.dat

description: :unav
DOI: 10.35003/jeno4t/t1ahj7
title: table-Figure6b-Height-Ra5e3.dat

description: :unav
DOI: 10.35003/jeno4t/ln2xes
title: table-Figure6c-Volume-B1.dat

description: :unav
DOI: 10.35003/jeno4t/jrs50s
title: table-Figure6b-Height-Ra2e4.dat

description: :unav
DOI: 10.35003/jeno4t/cqwjzy
title: table-Figure6d-Volume-EtaC.dat

description: :unav
DOI: 10.35003/jeno4t/xdfayx
title: table-Figure7a-time0.00856.dat

description: :unav
DOI: 10.35003/jeno4t/txlbm5
title: table-Figure6c-Height-B0.6.dat

description: :unav
DOI: 10.35003/jeno4t/bwzuki
title: table-Figure5b-noflux5.dat

description: :unav
DOI: 10.35003/jeno4t/rdh7n9
title: table-Figure7a-time0.04498.dat

description: :unav
DOI: 10.35003/jeno4t/thzo7t
title: table-Figure7d.dat

description: :unav
DOI: 10.35003/jeno4t/ic8g0t
title: table-Figure5c-noflux3.dat

description: :unav
DOI: 10.35003/jeno4t/f5wzeh
title: table-Figure3a-Temperature.dat

description: :unav
DOI: 10.35003/jeno4t/fgefww
title: table-Figure6b-Volume-Ra1e4.dat

description: :unav
DOI: 10.35003/jeno4t/f4q5mx
title: table-Figure5c-noflux15.dat

description: :unav
DOI: 10.35003/jeno4t/sukqbd
title: table-Figure2a-time0.0.dat

description: :unav
DOI: 10.35003/jeno4t/yab73b
title: table-Figure5b-influx.dat

description: :unav
DOI: 10.35003/jeno4t/vj4azr
title: table-Figure5b-noflux3.dat

description: :unav
DOI: 10.35003/jeno4t/gfeasg
title: table-Figure7e-linear.dat

description: :unav
DOI: 10.35003/jeno4t/1onwmt
title: table-Figure6d-Volume-alpha.dat

description: :unav
DOI: 10.35003/jeno4t/osqm5n
title: table-Figure6c-Height-B5.dat

description: :unav
DOI: 10.35003/jeno4t/nqmgw2
title: table-Figure5c-influx.dat

description: :unav
DOI: 10.35003/jeno4t/cht243
title: table-Figure6d-Volume-ref.dat

description: :unav
DOI: 10.35003/jeno4t/mwihnp
title: table-Figure6d-Height-alpha.dat

description: :unav
DOI: 10.35003/jeno4t/tpqp55
title: table-Figure5b-noflux10.dat

description: :unav
DOI: 10.35003/jeno4t/hjsjro
title: table-Figure5c-noflux10.dat

description: :unav
DOI: 10.35003/jeno4t/dn91ml
title: table-Figure6a-Volume-Le50.dat

description: :unav
DOI: 10.35003/jeno4t/pznvje
title: table-Figure4-Ra5e3.dat

description: :unav
DOI: 10.35003/jeno4t/ejr76o
title: table-Figure4h.dat

description: :unav
DOI: 10.35003/jeno4t/ytfayl
title: table-Figure6a-Volume-Le10.dat

description: :unav
DOI: 10.35003/jeno4t/gg8fuk
title: table-Figure3b.dat

description: :unav
DOI: 10.35003/jeno4t/pqorij
title: table-Figure6a-Height-Le500.dat

description: :unav
DOI: 10.35003/jeno4t/ov8xvf
title: table-Figure4-B2.dat

description: :unav
DOI: 10.35003/jeno4t/l3cy8l
title: table-Figure4-B0.6.dat

description: :unav
DOI: 10.35003/jeno4t/cl9a6c
title: table-Figure2a-time0.0039.dat

description: :unav
DOI: 10.35003/jeno4t/vmsjck
title: table-Figure6a-Height-Le10.dat

description: :unav
DOI: 10.35003/jeno4t/pakbwx
title: table-Figure4-Le500.dat

description: :unav
DOI: 10.35003/jeno4t/e3p0vy
title: table-Figure6a-Height-Le50.dat

description: :unav
DOI: 10.35003/jeno4t/53zpf0
title: table-Figure3a-Composition.dat

description: :unav
DOI: 10.35003/jeno4t/3qmhmp
title: table-Figure7a-time0.06134.dat

description: :unav
DOI: 10.35003/jeno4t/ys1cug
title: table-Figure7e-depleted.dat

description: :unav
DOI: 10.35003/jeno4t/gbaomh
title: table-Figure4-Le100.dat

description: :unav
DOI: 10.35003/jeno4t/nfjbxn
title: table-Figure7b-time0.00856.dat

description: :unav
DOI: 10.35003/jeno4t/vl0c5d
title: table-Figure6a-Volume-Le500.dat

description: :unav
DOI: 10.35003/jeno4t/gpevxy
title: table-Figure6d-Height-ref.dat

description: :unav
DOI: 10.35003/jeno4t/shpinx
title: table-Figure6d-Height-EtaC.dat

description: :unav
DOI: 10.35003/jeno4t/wej4jc
title: table-Figure7a-time0.02679.dat

description: :unav
DOI: 10.35003/jeno4t/rg96fx
title: table-Figure6c-Volume-B2.5.dat

description: :unav
DOI: 10.35003/jeno4t/jwgjba
title: table-Figure7b-time0.06134.dat

description: :unav
DOI: 10.35003/jeno4t/w9jj31
title: table-Figure4-Ra1e4.dat

description: :unav
DOI: 10.35003/jeno4t/b2zyzj
title: table-Figure4-Ra1e3.dat

description: :unav
DOI: 10.35003/jeno4t/wduiux
title: table-Figure5c-noflux5.dat

description: :unav
DOI: 10.35003/jeno4t/aupvck
title: table-Figure6c-Volume-B2.dat

description: :unav
DOI: 10.35003/jeno4t/dtbnok
title: table-Figure2a-time0.0011.dat

description: :unav
DOI: 10.35003/jeno4t/i6zvnf
title: table-Figure4-Ra2e4.dat

description: :unav
DOI: 10.35003/jeno4t/jwqleb
title: table-Figure6d-Volume-H1.dat

description: :unav
DOI: 10.35003/jeno4t/0mmo2o
title: table-Figure7b-time0.02679.dat

description: :unav
DOI: 10.35003/jeno4t/s8poof
title: table-Figure6c-Height-B1.dat

description: :unav
DOI: 10.35003/jeno4t/zsmf8s
title: table-Figure6c-Height-B1.2.dat

description: :unav
DOI: 10.35003/jeno4t/sshik1
title: table-Figure6b-Volume-Ra5e3.dat

description: :unav
DOI: 10.35003/jeno4t/twsnfe
title: table-Figure7b-time0.04498.dat

description: :unav
DOI: 10.35003/jeno4t/hccapt
title: table-Figure4-Le50.dat

description: :unav
DOI: 10.35003/jeno4t/pwofin
title: table-Figure2e.dat

description: :unav
DOI: 10.5281/zenodo.7670982
title: SHS-YouTube1300: A YouTube-based Cover Song Dataset (Crema-PCP Features)

description: These are the CREMA-PCP Features for our SHS-YouTube-1300 dataset and crawl. This crawl is based on the SHS100K dataset and contains YouTube videos of which a subset was annotated by crowd-workers and in-house annotators.
DOI: 10.5281/zenodo.7670983
title: SHS-YouTube1300: A YouTube-based Cover Song Dataset (Crema-PCP Features)

description: These are the CREMA-PCP Features for our SHS-YouTube-1300 dataset and crawl. This crawl is based on the SHS100K dataset and contains YouTube videos of which a subset was annotated by crowd-workers and in-house annotators.
DOI: 10.3886/e112839v1-138040
title: Replication data for: E-lections: Voting Behavior and the Internet

description: This paper analyzes the effects on voting behavior of information disseminated over the Internet. We address endogeneity in Internet availability by exploiting regional and technological peculiarities of the preexisting voice telephony network that hindered the roll-out of fixed-line infrastructure for high-speed Internet. We find negative effects of Internet availability on voter turnout, which we relate to a crowding-out of TV consumption and increased entertainment consumption. We find no evidence that the Internet systematically benefits specific parties, suggesting ideological self-segregation in online information consumption. Robustness tests, including placebo estimations from the pre-Internet period, support a causal interpretation of our results.
description: All voters in Germany.
DOI: 10.25345/c5057d306
title: MassIVE MSV000091853 - A phase-separated CO2-fixing pyrenoid proteome determined by TurboID in Chlamydomonas reinhardtii
title: Mass spectrometry data generated from TurboID-based proximity labeling of the Chlamydomonas phase-separated pyrenoid
DOI: 10.5519/qd.q7ah4631
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.19771911
title: Assessment of communication competence in acquired communication disorders: A systematic scoping review

description: Individuals with acquired communication disorders (ACDs) experience reduced ability to participate independently in activities of daily life, and maintain interpersonal relationships and psychosocial wellbeing. Communication interventions are designed to optimise communication competence in personally relevant everyday activities. However, the assessment tools speech-language pathologists (SLPs) typically utilise to evaluate communication competence in everyday life are not ideal. To explore the range and availability of assessments used in research to examine functional communication in adults with ACDs. Five databases (Medline, CINAHL, EMBASE, SCOPUS and PsycINFO) were searched to identify assessment or intervention studies evaluating functional communication in adults with ACDs. Functional communication tools utilised in each study were identified. Extracted tools were categorised according to type, target population, consideration of multimodal communication, person-specificity, consideration of context, availability, administration/analysis time and availability of normative/psychometric data. Forty functional communication assessment tools were included. Just over half the tools were performance-based (<i>n</i> = 25), examined different modes of communication (<i>n</i> = 26) and/or considered context (<i>n</i> = 23). Only 14 tools were person-specific. Many of the most comprehensive tools were out of print or considered excessively time consuming to administer and analyse. A paucity of accessible, time-efficient yet comprehensive tools to assess functional communication in ACDs may limit clinical practice and client outcomes. More versatile functional communication assessments incorporating individualised contexts, and the use of modern communication technologies are recommended.
DOI: 10.6084/m9.figshare.19771911.v1
title: Assessment of communication competence in acquired communication disorders: A systematic scoping review

description: Individuals with acquired communication disorders (ACDs) experience reduced ability to participate independently in activities of daily life, and maintain interpersonal relationships and psychosocial wellbeing. Communication interventions are designed to optimise communication competence in personally relevant everyday activities. However, the assessment tools speech-language pathologists (SLPs) typically utilise to evaluate communication competence in everyday life are not ideal. To explore the range and availability of assessments used in research to examine functional communication in adults with ACDs. Five databases (Medline, CINAHL, EMBASE, SCOPUS and PsycINFO) were searched to identify assessment or intervention studies evaluating functional communication in adults with ACDs. Functional communication tools utilised in each study were identified. Extracted tools were categorised according to type, target population, consideration of multimodal communication, person-specificity, consideration of context, availability, administration/analysis time and availability of normative/psychometric data. Forty functional communication assessment tools were included. Just over half the tools were performance-based (<i>n</i> = 25), examined different modes of communication (<i>n</i> = 26) and/or considered context (<i>n</i> = 23). Only 14 tools were person-specific. Many of the most comprehensive tools were out of print or considered excessively time consuming to administer and analyse. A paucity of accessible, time-efficient yet comprehensive tools to assess functional communication in ACDs may limit clinical practice and client outcomes. More versatile functional communication assessments incorporating individualised contexts, and the use of modern communication technologies are recommended.
DOI: 10.21942/uva.18857426
title: RCT PMK Nijmegen 2010

description: You can find the link to download the data here: <br> https://rdx-test.lab.surf.nl//access/10.21942/uva.18857426.v1
DOI: 10.34740/kaggle/dsv/5598808
title: AutoXGB