Attention: The autoQC service is now in beta mode. We are happy that you try out the service and give us feedback or report on probable bugs. Additionally we are working on several improvements and a "How To" documentation is coming soon.
autoQC is a tool that inlcudes classical and machine learning algorithms to support the quality control of arctic ocean temperature profile measurements. It has been developed in the M-VRE project (https://mosaic-vre.org). autoQC has been trained with the UDASH dataset and is based on works in the SalaciaML project (https://salacia-ml.awi.de/), which was published in Frontiers of Marine Sciences at SalaciaML. autoQC is developed by Dr. Mohamed Chouai, Felix Reimers and Dr. Sebastian Mieruch-Schnülle at the Alfred Wegener Institute (AWI) in Bremerhaven, Germany.
If you use autoQC, please cite: https://mvre.autoqc.cloud.awi.de
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UDASH arctic temperature profile with spike error.