cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.968043
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221027

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968067
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221212

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968068
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221223

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968069
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221214

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968070
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221213

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968071
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221215

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968072
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221217

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.1594/pangaea.968073
title: GEM-2 ice and platelet total thickness measurements for transect AFIN_ATKA_20221226

description: The snow+ice thickness (distance from the snow surface to the consolidated ice-platelet ice interface) and the underlying platelet ice thickness was measured by the electromagnetic induction (EM) method. On all transects, we used a multi-frequency EM instrument sensor (GEM-2 by Geophex Ltd) towed on a small sled behind a snowmobile (Hunkeler et al, 2016b). The instrument includes a real-time data processing unit including a GPS receiver which communicates with a pocket PC that is operates the sensor and records the EM and GPS data streams. The GEM-2 is a multi-frequency sensor that can transmit multiple configurable frequencies in the kHz range simultaneously. The sensor setup during AFIN used 5 frequencies with an approximately logarithmic spacing throughout the frequency range of the sensor (1.53, 5.31, 18.33, 63.03, and 93.09 kHz). The transect measurements are based on a sensor calibration, where the GEM-2 was placed in a zero-conductivity environment on the ice shelf before and after each transect to correct for signal offsets in instrument drift. The snow+ice and platelet ice thickness and conductivity retrieval of the calibrated GEM-2 surveys data was done by multi-frequncy inversion in the modified framework of the EMagPy (McLachlan et al., 2020) accounting for the bucking coil bias (Hunkeler at al., 2016a). To validate the retrieved thicknesses, we used the snow depth, ice thickness and platelet ice thickness from the drill hole measurements coincident with the GEM-2 transects. The coincident drill hole data can be found here: doi:10.1594/PANGAEA.968459. For more details we refer to the paper by Neudert et al, 2024: Improved sub-Ice Platelet Layer Mapping with multi-frequency EM Induction Sounding, in review at Journal of Applied Geophysics, Elsevier.
DOI: 10.15468/dl.ghuvsw
title: Occurrence Download

description: A dataset containing 7056 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Mallotus japonicus)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7056 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061408-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fma3v3
title: Occurrence Download

description: A dataset containing 1151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Piprites pileata (Temminck, 1822)"
 ]
}

 The dataset includes 1151 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025135-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4fvpe4
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Delosperma caespitosum L.Bolus"
 ]
}

 The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017903-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rfvcm2
title: Occurrence Download

description: A dataset listing the 16 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bassariscus astutus (Lichtenstein, 1830)"
 ]
}

 The dataset's 16 records were derived from 153 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0070075-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w4scvv
title: Occurrence Download

description: A dataset containing 14954 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Dasypus Linnaeus, 1758"
 ]
}

 The dataset includes 14954 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041088-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7pfx82
title: Occurrence Download

description: A dataset containing 8162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Diploria labyrinthiformis (Linnaeus, 1758)"
 ]
}

 The dataset includes 8162 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025151-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3brqu
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyperus divulsus Ridl."
 ]
}

 The dataset includes 56 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017915-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eaxzf5
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mikania weberbaueri Hieron."
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041121-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3thak9
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Marisora syntoma Mccranie, Matthews & Hedges, 2020"
 ]
}

 The dataset includes 66 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025165-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pebaxe
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Bidens subalternans DC."
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017906-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e205201v1
title: Civic Engagement Assignments and Political Efficacy

description: Survey responses to standard political efficacy battery<br><br> We examine
how to increase students’ self-reported feelings of political efficacy in
Introduction to U.S. Government courses. We test the effectiveness of civic
engagement assignments, such as writing a letter to your member of Congress or
attending a public meeting, in increasing political efficacy beyond simply
taking the course. Conducting pre and post-tests in both classes with
(treatment group) and without (control group) the civic engagement assignments
allows us to isolate the effect of the assignments. We find significant effects
for taking the course in both the treatment and control groups, confirming
existing research that taking Introduction to U.S. Government increases
students’ political efficacy. We also find treatment effects for multiple elements
of the standard political efficacy questionnaire. That our intervention had
these affects at a state university that is both a Hispanic Serving Institution
and a Minority Serving Institution indicates these types of civic engagement
assignments hold significant potential not just for increasing political
efficacy among students, but also increasing efficacy among historical
marginalized groups who typically participate in politics at lower rates than
White Americans.<br>
description: Intro to US Government students at CSUDH.