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8,191 to 8,200 of 11,133 Results

01_ReadMeFile.txt Jul 4, 2022 - TGO Ramfjordmoen Ionosonde Data July 1993 Plain Text - 2.3 KB - MD5: 6fc9fd029bf1a486d93dddc7aec3fe85
TGO_Ramfjordmoen_ionosonde_data_1993-07_SAO.zip Jul 4, 2022 - TGO Ramfjordmoen Ionosonde Data July 1993 ZIP Archive - 838.1 KB - MD5: a2e2078b32c52ad402288ba0c2511883
Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation May 22, 2019 Blanco Gonzalez, Enrique; Espeland, Sigurd Heiberg; Jentoft, Sissel; Hansen, Michael Møller; Robalo, Joana Isabel; Stenseth, Nils Christian; Jorde, Per Erik, 2019, "Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation", https://doi.org/10.18710/DSAPAP, DataverseNO, V2, UNF:6:GM79SmL+2M9XhptSGoPwVA== [fileUNF] This data file contains genotypic information at 11 microsatellite loci for parental analysis of corkwing wrasse (Symphodus melops). Additionally, it also contains phenotypic information from breeders.
00_ReadMe_File.txt Apr 24, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Plain Text - 2.0 KB - MD5: bcca28e39f678255976cc53c92eb3757
01_Interbreeding_cleaner_fish.tab May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Tabular Data - 16.6 KB - 12 Variables, 162 Observations - UNF:6:GM79SmL+2M9XhptSGoPwVA==
Interbreeding_cleaner_fish_Female.txt May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Plain Text - 13.0 KB - MD5: e6e71b652654cbcc6c1d1e3630e58675
Interbreeding_cleaner_fish_Male.txt May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Plain Text - 12.5 KB - MD5: a288306f7a8d61dddd67818107299b4d
Interbreeding_cleaner_fish_Offspring.txt May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Plain Text - 52.1 KB - MD5: 6bc71bfb72eaa8749c30ad4fddba5e13
Interbreeding_cleaner_fish_Phenotype.txt May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation Plain Text - 5.5 KB - MD5: 4d70187a22ea1bbd54be4ddc3e5dac96
Replication Data for: Auroral Image Classification with Deep Neural Networks Apr 14, 2020 Kvammen, Andreas; Wickstrøm, Kristoffer; McKay, Derek; Partamies, Noora, 2020, "Replication Data for: Auroral Image Classification with Deep Neural Networks", https://doi.org/10.18710/SSA38J, DataverseNO, V3 Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and A...

01_ReadMeFile.txt

Jul 4, 2022 - TGO Ramfjordmoen Ionosonde Data July 1993

Plain Text - 2.3 KB -

TGO_Ramfjordmoen_ionosonde_data_1993-07_SAO.zip

Jul 4, 2022 - TGO Ramfjordmoen Ionosonde Data July 1993

ZIP Archive - 838.1 KB -

Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

May 22, 2019

Blanco Gonzalez, Enrique; Espeland, Sigurd Heiberg; Jentoft, Sissel; Hansen, Michael Møller; Robalo, Joana Isabel; Stenseth, Nils Christian; Jorde, Per Erik, 2019, "Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation", https://doi.org/10.18710/DSAPAP, DataverseNO, V2, UNF:6:GM79SmL+2M9XhptSGoPwVA== [fileUNF]

This data file contains genotypic information at 11 microsatellite loci for parental analysis of corkwing wrasse (Symphodus melops). Additionally, it also contains phenotypic information from breeders.

00_ReadMe_File.txt

Apr 24, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Plain Text - 2.0 KB -

01_Interbreeding_cleaner_fish.tab

May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Tabular Data - 16.6 KB - 12 Variables, 162 Observations -

Interbreeding_cleaner_fish_Female.txt

May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Plain Text - 13.0 KB -

Interbreeding_cleaner_fish_Male.txt

May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Plain Text - 12.5 KB -

Interbreeding_cleaner_fish_Offspring.txt

May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Plain Text - 52.1 KB -

Interbreeding_cleaner_fish_Phenotype.txt

May 22, 2019 - Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation

Plain Text - 5.5 KB -

Replication Data for: Auroral Image Classification with Deep Neural Networks

Apr 14, 2020

Kvammen, Andreas; Wickstrøm, Kristoffer; McKay, Derek; Partamies, Noora, 2020, "Replication Data for: Auroral Image Classification with Deep Neural Networks", https://doi.org/10.18710/SSA38J, DataverseNO, V3

Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and A...

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