Metrics
1,837,820 Downloads
Contact Share
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

1 to 10 of 495 Results
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
make_w_gc.m
Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
MATLAB Source Code - 1.1 KB - MD5: 61bda33eb19fff36c06dc94044f2e65a
ML_dev_part1.ipynb
Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
Jupyter Notebook - 255.9 KB - MD5: 15e085e50a122a36c8cc28635f956db7
ML_dev_part2.ipynb
Feb 24, 2026 - Replication data for: Assessment of Data-Driven Techniques for Flow Rate Predictions in Sub-sea Oil Production
Jupyter Notebook - 240.4 KB - MD5: aec99d2af4b73cb120944552410a6f16
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.