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7,981 to 7,990 of 11,098 Results
28_GAM_models_nature.r
Jun 23, 2020 - Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis
R Syntax - 10.9 KB - MD5: 06e07f28c34980cd9585981e5b714aaa
R script for data analysis
29_Flickr_googlecloudvision_esmapping.r
Jun 23, 2020 - Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis
R Syntax - 4.3 KB - MD5: 06417d9600d78eb26067965420871f68
R script for data analysis
30_Flickr_validation_dataset.r
Jun 23, 2020 - Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis
R Syntax - 3.1 KB - MD5: 8e5ff065c7f0f17bda76876d74b0bffe
R script for data validation
31_Flickr_validation_interreliability.r
Jun 23, 2020 - Replication data for: Pan-Arctic analysis of cultural ecosystem services using social media and automated content analysis
R Syntax - 6.8 KB - MD5: 3db93ef908a5619d08599cd6aa61cc15
R script for data validation
Replication data for: One leaf for all: Chemical traits of single leaves measured at the leaf surface using near-infrared reflectance spectroscopy
Jun 23, 2020
Bråthen, Kari Anne; Petit Bon, Matteo; Böhner, Hanna; Kaino, Sissel; Moe, Torunn, 2020, "Replication data for: One leaf for all: Chemical traits of single leaves measured at the leaf surface using near-infrared reflectance spectroscopy", https://doi.org/10.18710/MHX1Z7, DataverseNO, V1
NIRS-based estimates of foliar chemical traits using two approaches. From NIRS-scans of dried, milled and tableted leaves and from NIRS-scans of full leaves dried flat.
01_Readmefile.txt
Jun 23, 2020 - Replication data for: One leaf for all: Chemical traits of single leaves measured at the leaf surface using near-infrared reflectance spectroscopy
Plain Text - 708 B - MD5: 16b7692d4626001a06253d600dff7fe4
Dataset.txt
Jun 23, 2020 - Replication data for: One leaf for all: Chemical traits of single leaves measured at the leaf surface using near-infrared reflectance spectroscopy
Plain Text - 920.5 KB - MD5: 4872d68f7acbb81f69160f292d7656cd
Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species
Jun 17, 2020
Brakestad, Anders; Jensen, Stig Rune; Wind, Peter; D'Alessandro, Marco; Genovese, Luigi; Hopmann, Kathrin Helen; Frediani, Luca, 2020, "Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species", https://doi.org/10.18710/KLQVOK, DataverseNO, V4, UNF:6:pBXeXp0l5KVVijVHeSqsdg== [fileUNF]
Introduction This Dataverse entry contains replication data for our journal article “Static polarizabilities at the basis set limit: A benchmark of 124 species” published in Journal of Chemical Theory and Computation. It contains highly precise static polarizabilities computed in...
000_README.txt
Jun 17, 2020 - Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species
Plain Text - 4.0 KB - MD5: 46d266e479637c773c585ee6843d39b7
correlation.ipynb
Jun 17, 2020 - Replication Data for: Static polarizabilities at the basis set limit: A benchmark of 124 species
Jupyter Notebook - 52.3 KB - MD5: 26d1a22021cc9ecaf57c9fb590e61fb6
Jupyter Notebook for generating Figure 5 in journal article.
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