cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.eun59d
title: Occurrence Download

description: A dataset containing 69236 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "Year 1837-1920"
 ]
}

 The dataset includes 69236 records from 374 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012971-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wxj7qm
title: Occurrence Download

description: A dataset containing 69 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anchoa parva",
 "Year 2000-2025"
 ]
}

 The dataset includes 69 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060238-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p59v5m
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anchoa starksi",
 "Year 2000-2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060240-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9dpnrx
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.3_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.3.24_1","matchCase":false},{"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 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060239-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5255/ukda-sn-858217
title: Preferences for Income and Wealth Limits: Evidence from a Survey Experiment, 2023

description: This is the replication package for the paper "Preferences for Income and Wealth Limits: Evidence from a Survey Experiment", published in the European Economic Review. The paper examines public support for imposing maximum limits on top incomes and wealth using a survey-based experiment with a large sample of US and German participants (N = 3,954). In addition to a baseline treatment in which US participants indicate whether they favour or oppose limits on CEOs’ compensation across several hypothetical scenarios, the design includes between-subject treatments to estimate the causal effects of two factors on limitarian preferences: concerns about potential efficiency losses from setting compensation limits (Treatment 2) and aversion to government intervention (Treatment 3). The study also tests whether the baseline findings extend to limits on entrepreneurial wealth accumulation (Treatment 4) and whether the results generalize to a different socio-political context using a German sample (Treatment 5). The package includes the original survey data, Stata replication code, a full survey transcript with variable labels and coding, and an accompanying read-me file describing the steps required to replicate the paper’s analysis.
DOI: 10.5281/zenodo.17986129
title: surface_albedos/Paragas25

description: Hemispherical reflectance data from Paragas et al. (2025).

Citation:

@article{Paragas_2025,
doi = {10.3847/1538-4357/ada9eb},
url = {https://doi.org/10.3847/1538-4357/ada9eb},
year = {2025},
month = {mar},
publisher = {The American Astronomical Society},
volume = {981},
number = {2},
pages = {130},
author = {Paragas, Kimberly and Knutson, Heather A. and Hu, Renyu and Ehlmann, Bethany L. and Alemanno, Giulia and Helbert, Jörn and Maturilli, Alessandro and Zhang, Michael and Iyer, Aishwarya and Rossman, George},
title = {A New Spectral Library for Modeling the Surfaces of Hot, Rocky Exoplanets},
journal = {The Astrophysical Journal},
abstract = {JWST’s MIRI LRS provides the first opportunity to spectroscopically characterize the surface compositions of close-in terrestrial exoplanets. Models for the bare-rock spectra of these planets often utilize a spectral library from R. Hu et al., which is based on room-temperature reflectance measurements of materials that represent archetypes of rocky planet surfaces. Here we present an expanded library that includes hemispherical reflectance measurements for a greater variety of compositions, varying textures (solid slab, coarsely crushed, and fine powder), as well as high-temperature (500–800 K) emissivity measurements for select samples. We incorporate this new library into version 6.3 of the open-source retrieval package PLATON and use it to show that planetary surfaces with similar compositions can have widely varying albedos and surface temperatures. We additionally demonstrate that changing the texture of a material can significantly alter its albedo, making albedo a poor proxy for surface composition. We identify key spectral features—the 5.6 μm olivine feature, the transparency feature, the Si-O stretching feature, and the Christiansen feature—that indicate silicate abundance and surface texture. We quantify the number of JWST observations needed to detect these features in the spectrum of the most favorable super-Earth target, LHS 3844 b, and revisit the interpretation of its Spitzer photometry. Lastly, we show that temperature-dependent changes in spectral features are likely undetectable at the precision of current exoplanet observations. Our results illustrate the importance of spectroscopically resolved thermal emission measurements, as distinct from surface albedo constraints, for characterizing the surface compositions of hot, rocky exoplanets.}
}
DOI: 10.5281/zenodo.17986128
title: surface_albedos/Paragas25

description: Hemispherical reflectance data from Paragas et al. (2025).

Citation:

@article{Paragas_2025,
doi = {10.3847/1538-4357/ada9eb},
url = {https://doi.org/10.3847/1538-4357/ada9eb},
year = {2025},
month = {mar},
publisher = {The American Astronomical Society},
volume = {981},
number = {2},
pages = {130},
author = {Paragas, Kimberly and Knutson, Heather A. and Hu, Renyu and Ehlmann, Bethany L. and Alemanno, Giulia and Helbert, Jörn and Maturilli, Alessandro and Zhang, Michael and Iyer, Aishwarya and Rossman, George},
title = {A New Spectral Library for Modeling the Surfaces of Hot, Rocky Exoplanets},
journal = {The Astrophysical Journal},
abstract = {JWST’s MIRI LRS provides the first opportunity to spectroscopically characterize the surface compositions of close-in terrestrial exoplanets. Models for the bare-rock spectra of these planets often utilize a spectral library from R. Hu et al., which is based on room-temperature reflectance measurements of materials that represent archetypes of rocky planet surfaces. Here we present an expanded library that includes hemispherical reflectance measurements for a greater variety of compositions, varying textures (solid slab, coarsely crushed, and fine powder), as well as high-temperature (500–800 K) emissivity measurements for select samples. We incorporate this new library into version 6.3 of the open-source retrieval package PLATON and use it to show that planetary surfaces with similar compositions can have widely varying albedos and surface temperatures. We additionally demonstrate that changing the texture of a material can significantly alter its albedo, making albedo a poor proxy for surface composition. We identify key spectral features—the 5.6 μm olivine feature, the transparency feature, the Si-O stretching feature, and the Christiansen feature—that indicate silicate abundance and surface texture. We quantify the number of JWST observations needed to detect these features in the spectrum of the most favorable super-Earth target, LHS 3844 b, and revisit the interpretation of its Spitzer photometry. Lastly, we show that temperature-dependent changes in spectral features are likely undetectable at the precision of current exoplanet observations. Our results illustrate the importance of spectroscopically resolved thermal emission measurements, as distinct from surface albedo constraints, for characterizing the surface compositions of hot, rocky exoplanets.}
}
DOI: 10.17026/ar/0fnzr9
title: PAN-00173664 - wire brooch with angular bow variant A1

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173664&lt;/p&gt;
description: Modified: 2025-11-18T17:40:32+01:00
DOI: 10.15468/dl.9gyk3s
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.17_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.17.1_1","matchCase":false},{"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 173 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060242-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tmh8c7
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anchoa tricolor",
 "Year 2000-2025"
 ]
}

 The dataset includes 33 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060244-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvdhd8
title: Occurrence Download

description: A dataset containing 3601 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tracheophyta)",
 "Geometry POLYGON ((13.01345 47.52272, 13.04845 47.52272, 13.04845 47.55772, 13.01345 47.55772, 13.01345 47.52272))"
 ]
}

 The dataset includes 3601 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060243-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mmmj8m
title: Occurrence Download

description: A dataset listing the 10638 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
}

 The dataset's 10638 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060224-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f4t2mh
title: Occurrence Download

description: A dataset listing the 51986 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-53.34665 2.4253,-50.43065 2.4253,-50.43065 4.81493,-53.34665 4.81493,-53.34665 2.4253))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 51986 records were derived from 688 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060229-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tmj83r
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anchoa helleri",
 "Year 2000-2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060245-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ay8zx3
title: Occurrence Download

description: A dataset containing 950764 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Benin",
 "Year 2000-2025"
 ]
}

 The dataset includes 950764 records from 338 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060198-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5fkrsj
title: Occurrence Download

description: A dataset containing 16899 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "GadmGid is one of (ESP.2_1, ESP.2.2_1, ESP.2.3_1, ESP.2.1_1)",
 "Geometry POLYGON((-2.07113 41.09753,-1.9758 41.10573,-1.84576 41.05046,-1.69342 40.93173,-1.68315 40.85054,-1.61312 40.79567,-1.61629 40.64257,-1.69906 40.64353,-1.74686 40.61703,-1.76051 40.51808,-1.86824 40.4291,-1.85767 40.35693,-1.78768 40.32018,-1.7888 40.25713,-1.75403 40.22973,-1.68352 40.22895,-1.55617 40.13734,-1.50903 40.14575,-1.50962 40.11873,-1.46331 40.0911,-1.29914 40.08881,-1.19434 40.06019,-1.23043 40.02471,-1.23159 39.97969,-1.19765 39.93412,-1.16304 39.91556,-0.97568 39.92144,-0.97779 39.84941,-0.92074 39.80336,-0.85098 39.79307,-0.75615 39.83632,-0.73071 39.89889,-0.77601 39.94481,-0.69232 39.99723,-0.57432 40.02184,-0.49814 40.18237,-0.3321 40.2237,-0.28154 40.3126,-0.22165 40.33819,-0.21869 40.41018,-0.2415 40.42874,-0.20506 40.45489,-0.20319 40.49988,-0.23559 40.57272,-0.23262 40.64471,-0.1728 40.66127,-0.17051 40.71526,0.06725 40.64062,0.10152 40.66851,0.20749 40.68013,0.34469 40.80046,0.31701 40.8989,0.3623 40.95399,0.36086 40.98998,0.34682 41.0437,0.28555 41.08731,0.44717 41.2171,0.4563 41.28935,0.43138 41.31582,0.4412 41.37008,0.4166 41.38754,0.41445 41.44153,0.46159 41.4606,0.51865 41.53389,0.49087 41.63236,0.41819 41.64876,0.40511 41.67548,0.45169 41.71255,0.49973 41.71361,0.53369 41.76838,0.59346 41.77865,0.67502 41.85238,0.67175 41.94238,0.73042 41.98858,0.78511 42.15175,0.77175 42.18752,0.83945 42.3329,0.78587 42.47597,0.82078 42.52166,0.82889 42.63889,0.67862 42.744,0.32542 42.71828,0.32349 42.76326,0.23723 42.77922,0.06673 42.76597,0.0558 42.73868,0 42.71922,0 42.6922,-0.04573 42.69339,-0.15176 42.77712,-0.15052 42.80411,-0.19979 42.79632,-0.2711 42.84306,-0.35667 42.84507,-0.38264 42.80965,-0.43189 42.80176,-0.51633 42.83064,-0.52999 42.79492,-0.55442 42.79544,-0.66099 42.88772,-0.72217 42.88895,-0.71985 42.95194,-0.74369 42.97042,-0.86716 42.94577,-0.91858 42.87468,-0.9207 42.81169,-0.99607 42.75,-1.05714 42.75105,-1.10763 42.69786,-1.18084 42.69905,-1.24338 42.64599,-1.24414 42.61899,-1.30557 42.6019,-1.35573 42.5486,-1.35738 42.48559,-1.40695 42.45027,-1.42159 42.35141,-1.45866 42.32489,-1.4602 42.26187,-1.48487 42.24419,-1.46413 42.09982,-1.40503 42.04497,-1.44303 41.97344,-1.55182 41.96586,-1.61117 42.01163,-1.69568 42.01262,-1.71929 42.0399,-1.81559 42.05895,-1.87601 42.05956,-1.91272 42.03289,-1.92722 41.88892,-1.89184 41.84355,-1.91729 41.76274,-1.86966 41.73526,-1.87013 41.70824,-1.95513 41.655,-2.05146 41.63782,-2.06451 41.56587,-2.04079 41.54766,-2.04172 41.48462,-2.13742 41.49439,-2.23484 41.35996,-2.21331 41.16165,-2.07113 41.09753),(-0.73855 40.01615,-0.7387 40.01167,-0.73853 40.01678,-0.73855 40.01615))"
 ]
 },
 "EventDate 2025-08-01-2025-12-19"
 ]
}

 The dataset includes 16899 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060230-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yadqey
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_0_GID","value":"ARG","matchCase":false},{"type":"equals","key":"GADM_LEVEL_1_GID","value":"ARG.17_1","matchCase":false},{"type":"equals","key":"GADM_LEVEL_2_GID","value":"ARG.17.7_1","matchCase":false},{"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 36 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060246-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/a7rbnd
title: PAN-00179894 - beacon lead

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00179894&lt;/p&gt;
description: Modified: 2025-11-18T10:29:53+01:00
DOI: 10.5281/zenodo.17986013
title: Selective Observation following Betrayal shapes the Social Inference Landscape

description: data (struct)

A MATLAB structure containing trial-wise variables describing behavior, eye movements, and task-related variables. Each cell strucuture (if there is) is a trial.

1. data.friendliness





F value during the inference phase.



2. data.friendlinessP



F value during the pursuit phase.


3. data.fchg





The change in friendliness (ΔF).



4. data.choiceItem





Participant’s choice on each trial.





1 = boost




0 = hinder





5. data.rewarded





Binary indicator of whether the trial resulted in a reward.



6. data.earnedMoney





Amount of money earned on each trial.



7. data.pvLength





Length (duration) of the inference phase (passive viweing=pv)



8. data.eyePos





Gaze position over time (one element = 1 time point = 1/60 second = 60Hz)



9. data.eyeSz





Pupil size over time.



10. data.avatar





Trajectory of the player-controlled avatar.



11. data.prey





Trajectory of the prey.



12. data.opponent





Trajectory of the opponent.



13. data.phase





Task phase labels over time



1 = inference phase

2 = item decision period

3 = pursuit phase




14. data.trial





Trial index.



15. data.block





Block index.



Experiment 1



1 = betrayal block

2 = unexpected-help block



Experiment 2



1 = betrayal increasing block

2 = betrayal decreasing block






16. data.Fhat





Time-resolved inferred F values during the inference phase from the autoregressive logistic regression model
DOI: 10.5281/zenodo.17986012
title: Selective Observation following Betrayal shapes the Social Inference Landscape

description: data (struct)

A MATLAB structure containing trial-wise variables describing behavior, eye movements, and task-related variables. Each cell strucuture (if there is) is a trial.

1. data.friendliness





F value during the inference phase.



2. data.friendlinessP



F value during the pursuit phase.


3. data.fchg





The change in friendliness (ΔF).



4. data.choiceItem





Participant’s choice on each trial.





1 = boost




0 = hinder





5. data.rewarded





Binary indicator of whether the trial resulted in a reward.



6. data.earnedMoney





Amount of money earned on each trial.



7. data.pvLength





Length (duration) of the inference phase (passive viweing=pv)



8. data.eyePos





Gaze position over time (one element = 1 time point = 1/60 second = 60Hz)



9. data.eyeSz





Pupil size over time.



10. data.avatar





Trajectory of the player-controlled avatar.



11. data.prey





Trajectory of the prey.



12. data.opponent





Trajectory of the opponent.



13. data.phase





Task phase labels over time



1 = inference phase

2 = item decision period

3 = pursuit phase




14. data.trial





Trial index.



15. data.block





Block index.



Experiment 1



1 = betrayal block

2 = unexpected-help block



Experiment 2



1 = betrayal increasing block

2 = betrayal decreasing block






16. data.Fhat





Time-resolved inferred F values during the inference phase from the autoregressive logistic regression model
DOI: 10.17028/rd.lboro.30870644
title: Numerical Modelling Data for Paper: Isoanemeity Predicts the Effect of Leaf Versus Stem Flexure on Plant Drag

description: This dataset keeps model data relating to a submission to Geophysical Research Letters, titled "Isoanemeity Predicts the Effect of Leaf Versus Stem Flexure on Plant Drag".For each of figures 2 to 5 in that manuscript, there is a corresponding csv / set of csvs herein.
DOI: 10.17028/rd.lboro.30870644.v1
title: Numerical Modelling Data for Paper: Isoanemeity Predicts the Effect of Leaf Versus Stem Flexure on Plant Drag

description: This dataset keeps model data relating to a submission to Geophysical Research Letters, titled "Isoanemeity Predicts the Effect of Leaf Versus Stem Flexure on Plant Drag".For each of figures 2 to 5 in that manuscript, there is a corresponding csv / set of csvs herein.
DOI: 10.13140/rg.2.2.22209.28001
title: Comoe basin hydro climatic data set, gridded data, monthly flow rates, GIS layers