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1 to 10 of 138,103 Results
Replication Data for: Finding common ground in commercial forests: sheep grazing, timber production, and carnivore fences
Feb 25, 2026 - University of Inland Norway
Malick-Wahls, Sarah Lou; Devineau, Olivier; Tofastrud, Morten; Zimmermann, Barbara, 2026, "Replication Data for: Finding common ground in commercial forests: sheep grazing, timber production, and carnivore fences", https://doi.org/10.18710/BZ2AWR, DataverseNO, V1
This dataset was created to support the article titled "Finding common ground in commercial forests: sheep grazing, timber production, and carnivore fences". We sampled clearcuts of regenerating spruce 29 July - 29 August 2024 in Inland and Trøndelag counties, Norway. Sheep grazing has the potential for positive impacts on commercial forestry throu...
00_README.txt
Feb 25, 2026 - Replication Data for: Finding common ground in commercial forests: sheep grazing, timber production, and carnivore fences
Plain Text - 6.7 KB - MD5: dbab1c61c960eff70699ec68702dbf32
forest_sheep_Malick.csv
Feb 25, 2026 - Replication Data for: Finding common ground in commercial forests: sheep grazing, timber production, and carnivore fences
Comma Separated Values - 97.2 KB - MD5: 5caf0741921fb24f2917b5c9f273e1ef
Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break
Feb 24, 2026 - University of Agder
Blanco Gonzalez, Enrique, 2026, "Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break", https://doi.org/10.18710/VPXHVP, DataverseNO, V1
This dataset contains all the information needed to reproduce the analyses performed in the manuscript "Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break" accepted for publication in Evolutionary Applications.
00_ReadMe.txt
Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break
Plain Text - 4.8 KB - MD5: 983da98a3fdee573d87018e73cd2518b
Description of the dataset.
Selection_against_hybrid_wrasses_GenotypeData.txt
Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break
Plain Text - 69.4 KB - MD5: f79f71b3bdca13bd6dfa4b65ee818a05
A table containing the genotype data saved as three-digit Genepop in txt format
Selection_against_hybrid_wrasses_Morphology.txt
Feb 24, 2026 - Replication Data for: Selection against hybrids maintains genetic divergence between populations of a coastal cleaner fish translocated across a genetic break
Plain Text - 6.8 KB - MD5: d56925fec42fed48375beaa3e24aaa8c
A table containing the morphological data in txt format
Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
Feb 24, 2026 - University of South-Eastern Norway
Neville Aloysius D’Souza; Pfeiffer, Carlos; Mirlekar, Gaurav, 2026, "Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production", https://doi.org/10.18710/KIJEWJ, DataverseNO, V1
The data set consists of simulated time‑series measurements from two gas‑lifted subsea oil wells, used to develop and evaluate data‑driven virtual flow metering (VFM) models for oil and gas flow rate prediction. Purpose: To assess a range of machine learning algorithms (10 methods, including LSTM, MLP, XGBoost, SVR, tree‑based and linear methods) f...
00_ReadMe.txt
Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
Plain Text - 4.1 KB - MD5: d876283a934a820f7703dd26e950e133
calculate_output.m
Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
MATLAB Source Code - 459 B - MD5: bfc538b18e25ef6c92be4f828244e4a7
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