cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vt5b7h
title: Occurrence Download

description: A dataset containing 519 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-65.57088 19.10914,33.61694 19.10914,33.61694 58.76729,-65.57088 58.76729,-34.83893 39.91126,-65.57088 19.10914))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rugulopteryx okamurae (E.Y.Dawson) I.K.Hwang, W.J.Lee & H.S.Kim, 2009"
 ]
}

 The dataset includes 519 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021207-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.24808
title: The targets and mechanisms of action of the AhR in NAFLD and other related diseases.
title: The targets and mechanisms of action of the AhR in NAFLD and other related diseases.

description:  The targets and mechanisms of action of the AhR in NAFLD and other related diseases.
description:  The targets and mechanisms of action of the AhR in NAFLD and other related diseases.
DOI: 10.57760/sciencedb.24806
title: Supplementary dataset for GMMAD2 database
title: Supplementary dataset for GMMAD2 database

description: Supplementary dataset for GMMAD2 database
description: Supplementary dataset for GMMAD2 database
DOI: 10.21233/a1hz-ew40
title: Keech Pond diatom surface sample dataset

description: Raw data for the Keech Pond diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.57760/sciencedb.24799
title: Shock metamorphic features of ordinary chondrite NWA 7458 and the formation mechanism of high pressure minerals
title: 普通球粒陨石NWA7458的冲击变质特征及其高压矿物形成机制

description: This Science data includes 7 figures and 2 tables.
description: This Science data includes 7 figures and 2 tables.
DOI: 10.57760/sciencedb.24791
title: Research on Shipborne Atmosphere Greenhouse Gas Column Concentration Measurement Method Based on Laser Heterodyne Spectroscopy
title: Research on Shipborne Atmosphere Greenhouse Gas Column Concentration Measurement Method Based on Laser Heterodyne Spectroscopy

description: Research on Shipborne Atmosphere Greenhouse Gas Column Concentration Measurement Method Based on Laser Heterodyne Spectroscopy
description: Research on Shipborne Atmosphere Greenhouse Gas Column Concentration Measurement Method Based on Laser Heterodyne Spectroscopy
DOI: 10.57760/sciencedb.24792
title: Deep Learning Network Asset Pricing Model in Corporate Bond Market
title: Deep Learning Network Asset Pricing Model in Corporate Bond Market

description: Journal of Business & Economic Statistics submit
description: Journal of Business & Economic Statistics submit
DOI: 10.57760/sciencedb.24789
title: Raw data for the article "Dual Mutations in MSMEG_0965 and MSMEG_1380 Confer High-Level Resistance to Bortezomib and Linezolid by Both Reducing Drug Intake and Increasing Efflux in Mycobacterium smegmatis"
title: Raw data for the article "Dual Mutations in MSMEG_0965 and MSMEG_1380 Confer High-Level Resistance to Bortezomib and Linezolid by Both Reducing Drug Intake and Increasing Efflux in Mycobacterium smegmatis"

description: This zip package includes all the raw data involving in the article "Dual Mutations in MSMEG_0965 and MSMEG_1380 Confer High-Level Resistance to Bortezomib and Linezolid by Both Reducing Drug Intake and Increasing Efflux in Mycobacterium smegmatis" submitted to the journal Communications Earth & Environment
description: This zip package includes all the raw data involving in the article "Dual Mutations in MSMEG_0965 and MSMEG_1380 Confer High-Level Resistance to Bortezomib and Linezolid by Both Reducing Drug Intake and Increasing Efflux in Mycobacterium smegmatis" submitted to the journal Communications Earth & Environment
DOI: 10.21233/5mrp-bx43
title: Whirligig Lake water chemistry dataset

description: Raw data for the Whirligig Lake water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.57760/sciencedb.24719
title: UV-Vis diffuse reflectance spectra, PL spectra, FTIR spectra, SEM images of prepared catalysts
title: UV-Vis diffuse reflectance spectra, PL spectra, FTIR spectra, SEM images of prepared catalysts

description: Solid-state ultraviolet-visible diffuse reflectance spectroscopy (UV-vis DRS) measures the light absorption properties and band gap width of catalysts. In this study, UV-3600 Plus spectrophotometer was used for testing.Fourier transform infrared spectroscopy (FT-IR) was used to analyze the different characteristic functional groups, molecular structure and chemical composition of the samples. FTS-3000 IR spectrometer was used in this study.Photoluminescence spectroscopy test (PL) was used to analyze the complexation process of photogenerated carriers. The instrument model used in this thesis is fluoro SENS9003.Scanning Electron Microscopy (SEM) is used to analyze the surface morphology, particle size, and other characteristics of materials. The equipment used in this study is Zeiss ULTRA Plus.
description: Solid-state ultraviolet-visible diffuse reflectance spectroscopy (UV-vis DRS) measures the light absorption properties and band gap width of catalysts. In this study, UV-3600 Plus spectrophotometer was used for testing.Fourier transform infrared spectroscopy (FT-IR) was used to analyze the different characteristic functional groups, molecular structure and chemical composition of the samples. FTS-3000 IR spectrometer was used in this study.Photoluminescence spectroscopy test (PL) was used to analyze the complexation process of photogenerated carriers. The instrument model used in this thesis is fluoro SENS9003.Scanning Electron Microscopy (SEM) is used to analyze the surface morphology, particle size, and other characteristics of materials. The equipment used in this study is Zeiss ULTRA Plus.
DOI: 10.21233/hn6g-n097
title: Summer Lake ostracode surface sample dataset

description: Raw data for the Summer Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.5281/zenodo.15363649
title: Review Buku Argonauts dan The west pacific
DOI: 10.5281/zenodo.15363650
title: Review Buku Argonauts dan The west pacific
DOI: 10.21233/h28x-8r05
title: Sandstone Lake ostracode surface sample dataset

description: Raw data for the Sandstone Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/qxsy-tj56
title: UNGAVA12 pollen surface sample dataset

description: Raw data for the UNGAVA12 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/0ywb-hk24
title: East Soldier Lake pollen dataset

description: Raw data for the East Soldier Lake pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/zwrm-fm22
title: NVJR17 pollen surface sample dataset

description: Raw data for the NVJR17 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/9rax-8226
title: 40DV35 macroinvertebrate dataset

description: Raw data for the 40DV35 macroinvertebrate dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/cnx9-n212
title: Riviere aux Outardes ostracode surface sample dataset

description: Raw data for the Riviere aux Outardes ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/8gbh-dw52
title: Arnett Mound [11Fl203] macroinvertebrate dataset

description: Raw data for the Arnett Mound [11Fl203] macroinvertebrate dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/v8dq-mc83
title: Swiss Trap S3 pollen surface sample dataset

description: Raw data for the Swiss Trap S3 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/xhkj-y531
title: Hidden Lake (NOCA) diatom dataset

description: Raw data for the Hidden Lake (NOCA) diatom dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/1p5h-tr88
title: Khanka Lake ostracode surface sample dataset

description: Raw data for the Khanka Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/pnv3-qs93
title: Hovenweep (Climax) pollen dataset

description: Raw data for the Hovenweep (Climax) pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/t9hq-8s30
title: Tena184 pollen surface sample dataset

description: Raw data for the Tena184 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.15468/dl.6kgdfs
title: Occurrence Download

description: A dataset containing 160119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lymnocryptes minimus (Brünnich, 1764)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 160119 records from 509 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021198-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/c2n1-7w59
title: Tucson Mountains, Pima Co., AZ plant macrofossil dataset

description: Raw data for the Tucson Mountains, Pima Co., AZ plant macrofossil dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/ng2w-vs19
title: Swamp diatom surface sample dataset

description: Raw data for the Swamp diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/xk54-c534
title: Vermillion River water chemistry dataset

description: Raw data for the Vermillion River water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/8qyj-ax08
title: Lake Waramaug diatom surface sample dataset

description: Raw data for the Lake Waramaug diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/72wn-jd36
title: Pembina River ostracode surface sample dataset

description: Raw data for the Pembina River ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/x9k5-4t58
title: Fairport Harbor [33LA5] macroinvertebrate dataset

description: Raw data for the Fairport Harbor [33LA5] macroinvertebrate dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/b41h-e607
title: Chuck Lake Site [CRG-237] vertebrate fauna dataset

description: Raw data for the Chuck Lake Site [CRG-237] vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/tmq0-gv04
title: Ganaraska River water chemistry dataset

description: Raw data for the Ganaraska River water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/8erk-z956
title: CHUS18 pollen surface sample dataset

description: Raw data for the CHUS18 pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/qtf9-zf76
title: Mohos pollen dataset

description: Raw data for the Mohos pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.25392/leicester.data.28905197
title: Data for "Geospatial Mechanistic Interpretability of Large Language Models"

description: This repository contains the data used for the book chapter by De Sabbata et al (2025), including the Free Gazetteer Data made available by GeoNames under CC BY 4.0, a file containing the names of the Italian provinces was made available by Michele Tizzoni under CC BY 4.0, and data derived from them using Mistral-7B-Instruct-v0.2, which was made available by the Mistral AI Team under Apache License 2.0. The code used to process the data is available via our related GitHub repository under MIT Licence.The Author Accepted Manuscript of "Geospatial Mechanistic Interpretability of Large Language Models" available on arXiv (arXiv:2505.03368).De Sabbata, S., Mizzaro, S. and Roitero, K. (2025) “Geospatial mechanistic interpretability of large language models,” in Janowicz, K. et al. (eds.) <i>Geography according to ChatGPT</i>. IOS Press (Frontiers in artificial intelligence and applications).<b>Abstract: </b>Large language models (LLMs) have demonstrated unprecedented capabilities across various natural language processing tasks. Their ability to process and generate viable text and code has made them ubiquitous in many fields, while their deployment as knowledge bases and ``reasoning'' tools remains an area of ongoing research. In geography, a growing body of literature has been focusing on evaluating LLMs' geographical knowledge and their ability to perform spatial reasoning. However, very little is still known about the internal functioning of these models, especially about how they process geographical information.In this chapter, we establish a novel framework for the study of geospatial mechanistic interpretability -- using spatial analysis to reverse engineer how LLMs handle geographical information. Our aim is to advance our understanding of the internal representations that these complex models generate while processing geographical information -- what one might call "how LLMs think about geographic information" if such phrasing was not an undue anthropomorphism.We first outline the use of probing in revealing internal structures within LLMs. We then introduce the field of mechanistic interpretability, discussing the superposition hypothesis and the role of sparse autoencoders in disentangling polysemantic internal representations of LLMs into more interpretable, monosemantic features.In our experiments, we use spatial autocorrelation to show how features obtained for placenames display spatial patterns related to their geographic location and can thus be interpreted geospatially, providing insights into how these models process geographical information. We conclude by discussing how our framework can help shape the study and use of foundation models in geography.
DOI: 10.25392/leicester.data.28905197.v1
title: Data for "Geospatial Mechanistic Interpretability of Large Language Models"

description: This repository contains the data used for the book chapter by De Sabbata et al (2025), including the Free Gazetteer Data made available by GeoNames under CC BY 4.0, a file containing the names of the Italian provinces was made available by Michele Tizzoni under CC BY 4.0, and data derived from them using Mistral-7B-Instruct-v0.2, which was made available by the Mistral AI Team under Apache License 2.0. The code used to process the data is available via our related GitHub repository under MIT Licence.The Author Accepted Manuscript of "Geospatial Mechanistic Interpretability of Large Language Models" available on arXiv (arXiv:2505.03368).De Sabbata, S., Mizzaro, S. and Roitero, K. (2025) “Geospatial mechanistic interpretability of large language models,” in Janowicz, K. et al. (eds.) <i>Geography according to ChatGPT</i>. IOS Press (Frontiers in artificial intelligence and applications).<b>Abstract: </b>Large language models (LLMs) have demonstrated unprecedented capabilities across various natural language processing tasks. Their ability to process and generate viable text and code has made them ubiquitous in many fields, while their deployment as knowledge bases and ``reasoning'' tools remains an area of ongoing research. In geography, a growing body of literature has been focusing on evaluating LLMs' geographical knowledge and their ability to perform spatial reasoning. However, very little is still known about the internal functioning of these models, especially about how they process geographical information.In this chapter, we establish a novel framework for the study of geospatial mechanistic interpretability -- using spatial analysis to reverse engineer how LLMs handle geographical information. Our aim is to advance our understanding of the internal representations that these complex models generate while processing geographical information -- what one might call "how LLMs think about geographic information" if such phrasing was not an undue anthropomorphism.We first outline the use of probing in revealing internal structures within LLMs. We then introduce the field of mechanistic interpretability, discussing the superposition hypothesis and the role of sparse autoencoders in disentangling polysemantic internal representations of LLMs into more interpretable, monosemantic features.In our experiments, we use spatial autocorrelation to show how features obtained for placenames display spatial patterns related to their geographic location and can thus be interpreted geospatially, providing insights into how these models process geographical information. We conclude by discussing how our framework can help shape the study and use of foundation models in geography.
DOI: 10.21233/cvkq-6094
title: Vestre Øykjamyrtjørn charcoal dataset

description: Raw data for the Vestre Øykjamyrtjørn charcoal dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/vg6v-mb80
title: Mulberry Mound [8OR10] vertebrate fauna dataset

description: Raw data for the Mulberry Mound [8OR10] vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.