rows { options { physical_type: PHYSICAL_STREAM_TYPE_QUADS max_name_table_size: 128 max_prefix_table_size: 16 max_datatype_table_size: 16 logical_type: LOGICAL_STREAM_TYPE_DATASETS version: 2 } } rows { prefix { value: "https://w3id.org/np/" } } rows { name { value: "RAuEy2gRxfXmDv6cNkbG86HNtXLNsBPdDiIpDlhyorVTc" } } rows { namespace { name: "this" value { prefix_id: 1 } } } rows { prefix { value: "https://w3id.org/np/RAuEy2gRxfXmDv6cNkbG86HNtXLNsBPdDiIpDlhyorVTc/" } } rows { name { } } rows { namespace { name: "sub" value { prefix_id: 2 } } } rows { prefix { value: "http://www.nanopub.org/nschema#" } } rows { namespace { name: "np" value { prefix_id: 3 name_id: 2 } } } rows { prefix { value: "http://purl.org/dc/terms/" } } rows { namespace { name: "dct" value { prefix_id: 4 name_id: 2 } } } rows { prefix { value: "http://purl.org/pav/" } } rows { namespace { name: "pav" value { prefix_id: 5 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/1999/02/22-rdf-syntax-ns#" } } rows { namespace { name: "rdf" value { prefix_id: 6 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/2002/07/owl#" } } rows { namespace { name: "owl" value { prefix_id: 7 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/2004/03/trix/rdfg-1/" } } rows { namespace { name: "rdfg" value { prefix_id: 8 name_id: 2 } } } rows { prefix { value: "http://purl.org/dc/elements/1.1/" } } rows { namespace { name: "dce" value { prefix_id: 9 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/2001/XMLSchema#" } } rows { namespace { name: "xsd" value { prefix_id: 10 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/2000/01/rdf-schema#" } } rows { namespace { name: "rdfs" value { prefix_id: 11 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/ns/prov#" } } rows { namespace { name: "prov" value { prefix_id: 12 name_id: 2 } } } rows { prefix { value: "http://purl.org/nanopub/x/" } } rows { namespace { name: "npx" value { prefix_id: 13 name_id: 2 } } } rows { name { value: "hasAssertion" } } rows { name { value: "assertion" } } rows { name { value: "Head" } } rows { quad { s_iri { prefix_id: 1 name_id: 1 } p_iri { prefix_id: 3 name_id: 3 } o_iri { prefix_id: 2 } g_iri { } } } rows { name { value: "hasProvenance" } } rows { name { value: "provenance" } } rows { quad { p_iri { prefix_id: 3 } o_iri { prefix_id: 2 } } } rows { name { value: "hasPublicationInfo" } } rows { name { value: "pubinfo" } } rows { quad { p_iri { prefix_id: 3 } o_iri { prefix_id: 2 } } } rows { name { value: "type" } } rows { name { value: "Nanopublication" } } rows { quad { p_iri { prefix_id: 6 } o_iri { prefix_id: 3 } } } rows { prefix { value: "http://eurovoc.europa.eu/" } } rows { name { value: "2919" } } rows { prefix { value: "http://schema.org/" } } rows { name { value: "description" } } rows { quad { s_iri { prefix_id: 14 } p_iri { prefix_id: 15 } o_literal { } g_iri { prefix_id: 2 name_id: 4 } } } rows { name { value: "name" } } rows { quad { p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "Environmental research" } } } rows { name { value: "DefinedTerm" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 15 name_id: 15 } } } rows { name { value: "3941" } } rows { quad { s_iri { prefix_id: 14 } p_iri { prefix_id: 15 name_id: 13 } o_literal { } } } rows { quad { p_iri { } o_literal { lex: "Life sciences" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 15 name_id: 15 } } } rows { name { value: "3946" } } rows { quad { s_iri { prefix_id: 14 name_id: 17 } p_iri { prefix_id: 15 name_id: 13 } o_literal { } } } rows { quad { p_iri { } o_literal { lex: "Physical sciences" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 15 name_id: 15 } } } rows { prefix { value: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/#" } } rows { name { value: "enrichment_service-account-enrichment" } } rows { quad { s_iri { prefix_id: 16 name_id: 18 } p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "service-account-enrichment" } } } rows { prefix { id: 4 value: "http://xmlns.com/foaf/0.1/" } } rows { name { value: "Agent" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 19 } } } rows { prefix { value: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/" } } rows { name { value: "about" } } rows { quad { s_iri { prefix_id: 5 name_id: 2 } p_iri { prefix_id: 15 name_id: 20 } o_iri { prefix_id: 14 name_id: 12 } } } rows { quad { o_iri { name_id: 16 } } } rows { quad { o_iri { } } } rows { name { value: "author" } } rows { prefix { id: 7 } } rows { name { value: "mailto:chakravarthi.kanduri@rohub.com" } } rows { quad { p_iri { prefix_id: 15 name_id: 21 } o_iri { prefix_id: 7 } } } rows { name { value: "contentSize" } } rows { datatype { value: "http://www.w3.org/2001/XMLSchema#integer" } } rows { quad { p_iri { prefix_id: 15 } o_literal { lex: "8221" datatype: 1 } } } rows { name { value: "contentUrl" } } rows { quad { p_iri { } o_literal { lex: "https://api.rohub.org/api/ros/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/crate/download/" } } } rows { name { value: "creator" } } rows { name { value: "mailto:georgehadib@gmail.com" } } rows { quad { p_iri { } o_iri { prefix_id: 7 } } } rows { name { value: "dateCreated" } } rows { quad { p_iri { prefix_id: 15 } o_literal { lex: "2022-03-22 03:39:42.950131+00:00" } } } rows { name { value: "dateModified" } } rows { quad { p_iri { } o_literal { lex: "2025-03-05 00:46:58.413525+00:00" } } } rows { name { value: "datePublished" } } rows { quad { p_iri { } o_literal { lex: "2022-03-22 03:39:42.950131+00:00" } } } rows { quad { p_iri { name_id: 13 } o_literal { lex: "This upload contains all the code and software used in the manuscript \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\". The README file provides guidance on how to execute the code to reproduce the findings. Note that the software wrapped inside this upload have their own license statements, but included in this upload just for the sake of freezing the versions used in this study. " } } } rows { name { value: "encodingFormat" } } rows { quad { p_iri { name_id: 30 } o_literal { lex: "application/ld+json" } } } rows { name { value: "hasPart" } } rows { prefix { value: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/folders/" } } rows { name { value: "3fd0b05e-5003-4e53-8c20-3080a50861c0" } } rows { quad { p_iri { } o_iri { prefix_id: 8 } } } rows { name { value: "55b8c393-10da-43b7-a536-2f3c138be0c5" } } rows { quad { o_iri { } } } rows { name { value: "8ba01db0-38d4-40a4-a72f-10221d862c40" } } rows { quad { o_iri { } } } rows { name { value: "a7352257-4307-49a3-bbf8-cde414797045" } } rows { quad { o_iri { } } } rows { name { value: "identifier" } } rows { quad { p_iri { prefix_id: 15 } o_literal { lex: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd" } } } rows { name { value: "license" } } rows { prefix { value: "https://choosealicense.com/no-permission/" } } rows { quad { p_iri { } o_iri { prefix_id: 9 name_id: 2 } } } rows { quad { p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\"" } } } rows { prefix { value: "http://w3id.org/ro-id/rohub/model#" } } rows { name { value: "creation_mode" } } rows { quad { p_iri { prefix_id: 10 name_id: 38 } o_literal { lex: "MANUAL" } } } rows { prefix { value: "http://w3id.org/ro/earth-science#" } } rows { name { value: "Concept" } } rows { quad { p_iri { prefix_id: 11 } o_literal { lex: "baseline" } } } rows { quad { o_literal { lex: "category" } } } rows { quad { o_literal { lex: "code" } } } rows { quad { o_literal { lex: "computer code" } } } rows { quad { o_literal { lex: "finding" } } } rows { quad { o_literal { lex: "guidance" } } } rows { quad { o_literal { lex: "limit" } } } rows { quad { o_literal { lex: "machine learning" } } } rows { quad { o_literal { lex: "receptor" } } } rows { quad { o_literal { lex: "repertory" } } } rows { quad { o_literal { lex: "software" } } } rows { quad { o_literal { lex: "upload" } } } rows { name { value: "FieldOfResearch" } } rows { quad { p_iri { } o_literal { lex: "earth sciences" } } } rows { name { value: "IPTC" } } rows { quad { p_iri { } o_literal { lex: "Financial statement" } } } rows { quad { o_literal { lex: "IT-computer sciences" } } } rows { quad { o_literal { lex: "Software" } } } rows { name { value: "Lemma" } } rows { quad { p_iri { } o_literal { lex: "classification" } } } rows { quad { o_literal { lex: "code" } } } rows { quad { o_literal { lex: "limit" } } } rows { quad { o_literal { lex: "machine learning" } } } rows { quad { o_literal { lex: "repertoire" } } } rows { quad { o_literal { lex: "software" } } } rows { quad { o_literal { lex: "upload" } } } rows { name { value: "NASA" } } rows { quad { p_iri { } o_literal { lex: "mathematical and computer sciences" } } } rows { name { value: "Phrase" } } rows { quad { p_iri { } o_literal { lex: "baseline performance" } } } rows { quad { o_literal { lex: "license statement" } } } rows { quad { o_literal { lex: "machine learning model" } } } rows { quad { o_literal { lex: "receptor repertoire classification" } } } rows { quad { o_literal { lex: "repertoire classification" } } } rows { name { value: "Sentence" } } rows { quad { p_iri { } o_literal { lex: "Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\" This upload contains all the code and software used in the manuscript \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\" The README file provides guidance on how to execute the code to reproduce the findings." } } } rows { quad { o_literal { lex: "Note that the software wrapped inside this upload have their own license statements, but included in this upload just for the sake of freezing the versions used in this study. nbsp;" } } } rows { prefix { value: "http://purl.org/wf4ever/ro#" } } rows { name { value: "ResearchObject" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 12 name_id: 46 } } } rows { prefix { value: "http://purl.org/wf4ever/roevo#" } } rows { name { value: "LiveRO" } } rows { quad { o_iri { prefix_id: 13 } } } rows { name { value: "Dataset" } } rows { quad { o_iri { prefix_id: 15 } } } rows { name { value: "DataResearchObject" } } rows { quad { o_iri { prefix_id: 11 } } } rows { prefix { id: 1 value: "https://w3id.org/ro/terms/earth-science#" } } rows { quad { o_iri { prefix_id: 1 name_id: 49 } } } rows { prefix { id: 3 value: "https://w3id.org/contentdesc#" } } rows { name { value: "Domain" } } rows { quad { p_iri { prefix_id: 3 } o_literal { lex: "computer science" } } } rows { quad { o_literal { lex: "software" } } } rows { prefix { id: 2 value: "https://www.w3.org/ns/iana/link-relations/relation#" } } rows { name { value: "cite-as" } } rows { quad { p_iri { prefix_id: 2 } o_literal { lex: "Chakravarthi Kanduri. \"Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\".\" ROHub. Mar 22 ,2022. https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd." } } } rows { prefix { id: 16 value: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/resources/" } } rows { name { value: "b9c63393-0d5d-4551-b5ee-8297a1ca3c16" } } rows { quad { s_iri { prefix_id: 8 name_id: 32 } p_iri { prefix_id: 15 name_id: 31 } o_iri { prefix_id: 16 name_id: 52 } } } rows { quad { p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "data" } } } rows { prefix { id: 4 value: "http://purl.org/wf4ever/wf4ever#" } } rows { name { value: "Folder" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 53 } } } rows { quad { o_iri { prefix_id: 15 name_id: 48 } } } rows { quad { s_iri { prefix_id: 8 name_id: 33 } p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "raw data" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 53 } } } rows { quad { o_iri { prefix_id: 15 name_id: 48 } } } rows { quad { s_iri { prefix_id: 8 name_id: 34 } p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "metadata" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 53 } } } rows { quad { o_iri { prefix_id: 15 name_id: 48 } } } rows { quad { s_iri { prefix_id: 8 name_id: 35 } p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "biblio" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 53 } } } rows { quad { o_iri { prefix_id: 15 name_id: 48 } } } rows { prefix { value: "http://purl.org/dc/terms/" } } rows { name { value: "bibliographicCitation" } } rows { quad { s_iri { prefix_id: 16 name_id: 52 } p_iri { prefix_id: 5 name_id: 54 } o_literal { lex: "Kanduri, C. (2021).Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\" [Data set]. Norstore. https://doi.org/10.11582/2021.00038" } } } rows { name { value: "rightsHolder" } } rows { quad { p_iri { } o_literal { lex: "Chakravarthi Kanduri" } } } rows { quad { p_iri { name_id: 10 } o_literal { lex: "Software" } } } rows { quad { p_iri { prefix_id: 15 name_id: 21 } o_iri { prefix_id: 7 name_id: 26 } } } rows { quad { p_iri { prefix_id: 15 name_id: 24 } o_literal { lex: "https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00038" } } } rows { quad { p_iri { } o_iri { prefix_id: 7 } } } rows { quad { p_iri { prefix_id: 15 } o_literal { lex: "2021-05-12 00:00:00" } } } rows { quad { p_iri { } o_literal { lex: "2022-03-22 03:40:01.071302+00:00" } } } rows { quad { p_iri { name_id: 13 } o_literal { lex: "This upload contains all the code and software used in the manuscript \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\". The README file provides guidance on how to execute the code to reproduce the findings. Note that the software wrapped inside this upload have their own license statements, but included in this upload just for the sake of freezing the versions used in this study. " } } } rows { quad { p_iri { name_id: 37 } o_iri { prefix_id: 9 name_id: 2 } } } rows { quad { p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\"" } } } rows { name { value: "sdDatePublished" } } rows { quad { p_iri { name_id: 56 } o_literal { lex: "2021-05-12 00:00:00" } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 4 name_id: 48 } } } rows { name { value: "Resource" } } rows { quad { o_iri { name_id: 57 } } } rows { name { value: "MediaObject" } } rows { quad { o_iri { prefix_id: 15 } } } rows { prefix { id: 14 value: "https://schema.org/" } } rows { name { value: "maintainer" } } rows { quad { p_iri { prefix_id: 14 } o_literal { lex: "Chakravarthi Kanduri" } } } rows { prefix { id: 10 value: "https://w3id.org/ro-id/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/" } } rows { name { value: "ro-crate-metadata.json" } } rows { name { value: "conformsTo" } } rows { prefix { id: 12 value: "https://w3id.org/ro/crate/" } } rows { name { value: "1.1" } } rows { quad { s_iri { prefix_id: 10 } p_iri { prefix_id: 5 } o_iri { prefix_id: 12 } } } rows { quad { p_iri { prefix_id: 15 name_id: 20 } o_iri { prefix_id: 10 name_id: 2 } } } rows { name { value: "CreativeWork" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 15 name_id: 63 } } } rows { name { value: "email" } } rows { quad { s_iri { prefix_id: 7 name_id: 22 } p_iri { prefix_id: 15 name_id: 64 } o_literal { lex: "chakravarthi.kanduri@rohub.com" } } } rows { quad { p_iri { name_id: 14 } o_literal { lex: "Chakravarthi Kanduri" } } } rows { prefix { value: "http://xmlns.com/foaf/0.1/" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 13 name_id: 19 } } } rows { quad { s_iri { prefix_id: 7 name_id: 26 } p_iri { prefix_id: 15 name_id: 14 } o_literal { lex: "Geo H." } } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 13 name_id: 19 } } } rows { prefix { id: 11 value: "https://w3id.org/np/RAuEy2gRxfXmDv6cNkbG86HNtXLNsBPdDiIpDlhyorVTc/" } } rows { prefix { id: 1 value: "http://www.w3.org/ns/prov#" } } rows { name { value: "wasDerivedFrom" } } rows { prefix { id: 3 value: "https://api.rohub.org/api/ros/3f7df05b-ac98-4ff8-96fe-4b4572aaa7cd/crate/download/" } } rows { quad { s_iri { prefix_id: 11 name_id: 4 } p_iri { prefix_id: 1 name_id: 65 } o_iri { prefix_id: 3 name_id: 60 } g_iri { prefix_id: 11 name_id: 7 } } } rows { prefix { id: 2 value: "https://w3id.org/np/" } } rows { name { value: "created" } } rows { datatype { value: "http://www.w3.org/2001/XMLSchema#dateTime" } } rows { quad { s_iri { prefix_id: 2 name_id: 1 } p_iri { prefix_id: 5 name_id: 66 } o_literal { lex: "2026-03-03T16:10:36.590+01:00" datatype: 2 } g_iri { prefix_id: 11 name_id: 9 } } } rows { prefix { id: 8 value: "https://w3id.org/kpxl/gen/terms/" } } rows { name { value: "RoCrateBot" } } rows { quad { p_iri { prefix_id: 5 name_id: 25 } o_iri { prefix_id: 8 name_id: 67 } } } rows { prefix { id: 16 value: "http://purl.org/nanopub/x/" } } rows { name { value: "introduces" } } rows { quad { p_iri { prefix_id: 16 } o_iri { prefix_id: 10 name_id: 2 } } } rows { name { value: "RoCrateNanopub" } } rows { quad { p_iri { prefix_id: 6 name_id: 10 } o_iri { prefix_id: 16 name_id: 69 } } } rows { prefix { id: 9 value: "http://www.w3.org/2000/01/rdf-schema#" } } rows { name { value: "label" } } rows { quad { p_iri { prefix_id: 9 } o_literal { lex: "Code and software used in the article \"Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification\"" } } } rows { name { value: "sig" } } rows { name { value: "hasAlgorithm" } } rows { quad { s_iri { prefix_id: 11 } p_iri { prefix_id: 16 } o_literal { lex: "RSA" } } } rows { name { value: "hasPublicKey" } } rows { quad { p_iri { } o_literal { lex: "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAxszSDYX5tuCSkP7UiCtftYPFNQVTjgNu0I5fwdML2DLRDlp0xzmsQXRk8oHuvwGvG1aMjj6cpUqO+0rz2Sg/wvHOgUpkRH8VJXvmlkhafMLCMtUtk5JIx7e+fkzCby+fnmD7kMkGLrT+OaExWwEDmNlCAt0TPKcHSdwsjso2isXjtAsGevyCMke8ufnFYpjs746JES1eNzVnHnn2Kp/lqcm60GM+J8dLgRZp7fX0anW098xhKym6+xXFzqeju0vYRIHBPerv+r7skWxwk+a7Sd8msqVeYEv6NTqnyWvyWb6Yh8cvj04N6qm/T6C5FUPLQhzSaQgMVMU6yLqjPuu9DwIDAQAB" } } } rows { name { value: "hasSignature" } } rows { quad { p_iri { } o_literal { lex: "gnoFWL0+gAQwIkm/LtXntvOG3S8e8rf6wfcJqx/GZprMWdoaQbxJW3g5xoVUn10UzULseosmR55MXQyYLCrv8bDtMmqDAX6LRDJSosoVL/kTFhu3A6EVL0WnFrMwDcRpnjc0vNYumLEQ9IF9PXmQAHXENapNM6uwNSfhRfHWvIyH35j3/GXg7jVImFyEp367ZIOL2C6vEAhMzX3dY8Ng53WBQbyISvIWSd6ttoi2qBrN/YIhLshNSWa7a87RwU2gJAiEsAk46SdPcXLh9MwhZYbyq5fd/janskNB7LG5JCqVzaSpM9R3kEcgURBnEYGxfkfPUCCimJt4QufIBE6vPA==" } } } rows { name { value: "hasSignatureTarget" } } rows { quad { p_iri { } o_iri { prefix_id: 2 name_id: 1 } } } rows { name { value: "signedBy" } } rows { quad { p_iri { prefix_id: 16 name_id: 76 } o_iri { prefix_id: 8 name_id: 67 } } }