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https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Lemma ground truth https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Lemma machine learning https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Lemma use case https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#NASA geosciences https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Phrase ML method https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Phrase immuneML use case 3 https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Phrase machine learning method https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Phrase specification file https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Phrase synthetic data https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Sentence This dataset contains the original specification files and complete results for immuneML use case 3: Benchmarking machine learning methods for AIRR classification on ground-truth synthetic data. https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Sentence To use the dataset you should follow the guidelines in the README.txt file contained within the dataset. https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://w3id.org/ro/earth-science#Sentence immuneML use case 3: Benchmarking ML methods for AIRR classification on ground-truth synthetic data. https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/ro#ResearchObject https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roevo#LiveRO https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://w3id.org/ro/earth-science#DataResearchObject https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://w3id.org/ro/terms/earth-science#DataResearchObject https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ https://w3id.org/contentdesc#Domain computer science https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/ https://www.w3.org/ns/iana/link-relations/relation#cite-as Lonneke Scheffer. "immuneML use case 3: Benchmarking ML methods for AIRR classification on ground-truth synthetic data.." ROHub. Mar 22 ,2022. https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40. https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/5428e9db-a593-4fae-8506-bfb6b977ae8f http://schema.org/name raw data https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/5428e9db-a593-4fae-8506-bfb6b977ae8f http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Folder https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/5428e9db-a593-4fae-8506-bfb6b977ae8f http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/7444e5b0-d102-443e-bc75-5199e9526c20 http://schema.org/name biblio https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/7444e5b0-d102-443e-bc75-5199e9526c20 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Folder https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/7444e5b0-d102-443e-bc75-5199e9526c20 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/b10d767d-8b59-4bf9-9132-4235abb32b69 http://schema.org/name metadata https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/b10d767d-8b59-4bf9-9132-4235abb32b69 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Folder https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/b10d767d-8b59-4bf9-9132-4235abb32b69 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/ddcd249b-9c74-487a-9ca0-3062dcacf6f4 http://schema.org/hasPart https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/ddcd249b-9c74-487a-9ca0-3062dcacf6f4 http://schema.org/name data https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/ddcd249b-9c74-487a-9ca0-3062dcacf6f4 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Folder https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/folders/ddcd249b-9c74-487a-9ca0-3062dcacf6f4 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://purl.org/dc/terms/bibliographicCitation Scheffer, L. (2021).immuneML use case 3: Benchmarking ML methods for AIRR classification on ground-truth synthetic data. [Data set]. Norstore. https://doi.org/10.11582/2021.00005 https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://purl.org/dc/terms/rightsHolder Lonneke Scheffer https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://purl.org/dc/terms/type Simulation https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/author mailto:georgehadib@gmail.com https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/contentUrl https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00005 https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/creator mailto:georgehadib@gmail.com https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/dateCreated 2021-02-08 00:00:00 https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/dateModified 2022-03-22 02:26:39.884078+00:00 https://w3id.org/ro-id/2bea96a2-5153-4937-9a34-78fbd6967d40/resources/361a6bc2-67b4-4f20-87ae-4a5a4f90ba9e http://schema.org/description This dataset contains the original specification files and complete results for immuneML use case 3: Benchmarking machine learning methods for AIRR classification on ground-truth synthetic data. 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