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/sciencelive/np/" } } rows { name { value: "RAW3U5bhevQdUMc51N_QsJSuCrV8j8QauGh9cU6H0o-2Q" } } rows { namespace { name: "this" value { prefix_id: 1 } } } rows { prefix { value: "https://w3id.org/sciencelive/np/RAW3U5bhevQdUMc51N_QsJSuCrV8j8QauGh9cU6H0o-2Q/" } } 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://www.w3.org/1999/02/22-rdf-syntax-ns#" } } rows { namespace { name: "rdf" value { prefix_id: 4 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/ns/prov#" } } rows { namespace { name: "prov" value { prefix_id: 5 name_id: 2 } } } rows { prefix { value: "http://purl.org/nanopub/x/" } } rows { namespace { name: "npx" value { prefix_id: 6 name_id: 2 } } } rows { prefix { value: "http://purl.org/dc/terms/" } } rows { namespace { name: "dc" value { prefix_id: 7 name_id: 2 } } } rows { prefix { value: "http://www.w3.org/2001/XMLSchema#" } } rows { namespace { name: "xsd" value { prefix_id: 8 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: 4 } o_iri { prefix_id: 3 } } } rows { name { value: "supervised-pretraining" } } rows { prefix { value: "https://w3id.org/sciencelive/o/terms/" } } rows { name { value: "FORRT-Replication-Study" } } rows { quad { s_iri { prefix_id: 2 } o_iri { prefix_id: 9 } g_iri { prefix_id: 2 name_id: 4 } } } rows { name { value: "Replication-Study" } } rows { quad { o_iri { prefix_id: 9 name_id: 14 } } } rows { prefix { value: "http://www.w3.org/2000/01/rdf-schema#" } } rows { name { value: "label" } } rows { quad { p_iri { prefix_id: 10 } o_literal { lex: "Supervised pretraining as alternative to episodic meta-learning for satellite imagery classification" } } } rows { prefix { value: "http://www.w3.org/2004/02/skos/core#" } } rows { name { value: "related" } } rows { prefix { value: "http://www.wikidata.org/entity/" } } rows { name { value: "Q110797734" } } rows { quad { p_iri { prefix_id: 11 } o_iri { prefix_id: 12 } } } rows { name { value: "Q197536" } } rows { quad { o_iri { } } } rows { name { value: "Q334384" } } rows { quad { o_iri { } } } rows { name { value: "Q6027324" } } rows { quad { o_iri { } } } rows { name { value: "hasDeviationDescription" } } rows { quad { p_iri { prefix_id: 9 } o_literal { lex: "Guo et al. trained Prototypical Networks episodically (40,000 episodes, approximately 3 hours). We replaced episodic training with standard supervised classification (10 epochs, approximately 15 minutes). Same backbone and image resolution. This tests whether the training method matters for cross-domain transfer, or whether the backbone features alone are sufficient." } } } rows { name { value: "hasDiscipline" } } rows { name { value: "Q21198" } } rows { quad { p_iri { } o_iri { prefix_id: 12 } } } rows { name { value: "hasMethodologyDescription" } } rows { quad { p_iri { prefix_id: 9 } o_literal { lex: "We trained a ResNet-10 backbone (4.9 million parameters, 224\303\227224 pixel images) using standard supervised classification on mini-ImageNet\'s 64 object categories for 10 epochs with data augmentation. At test time, we froze the backbone and used Prototypical Network-style nearest-prototype classification on EuroSAT (27,000 real Sentinel-2 satellite patches). This approach requires no meta-learning framework \342\200\224 only standard PyTorch classification training. Evaluation over 100 random 5-way tasks with 5, 20, and 50 labeled examples." } } } rows { name { value: "hasScopeDescription" } } rows { quad { p_iri { } o_literal { lex: "Testing whether standard supervised pretraining \342\200\224 training a model to classify everyday objects using conventional classification \342\200\224 achieves comparable cross-domain few-shot accuracy on satellite imagery to the episodic meta-learning approach used by Guo et al. (2020). " } } } rows { name { value: "targetsClaim" } } rows { prefix { value: "https://w3id.org/np/RAC32x9lWdLTKRpiz7utsMmLf0_JzadtA4kCvvbrJ_KK8/" } } rows { quad { p_iri { } o_iri { prefix_id: 13 name_id: 12 } } } rows { name { value: "wasAttributedTo" } } rows { prefix { value: "https://orcid.org/" } } rows { name { value: "0000-0002-1784-2920" } } rows { quad { s_iri { prefix_id: 2 name_id: 4 } p_iri { prefix_id: 5 name_id: 27 } o_iri { prefix_id: 14 } g_iri { prefix_id: 2 name_id: 7 } } } rows { prefix { value: "http://xmlns.com/foaf/0.1/" } } rows { name { value: "name" } } rows { quad { s_iri { prefix_id: 14 name_id: 28 } p_iri { prefix_id: 15 } o_literal { lex: "Anne Fouilloux" } g_iri { prefix_id: 2 name_id: 9 } } } rows { name { value: "created" } } rows { datatype { value: "http://www.w3.org/2001/XMLSchema#dateTime" } } rows { quad { s_iri { prefix_id: 1 name_id: 1 } p_iri { prefix_id: 7 name_id: 30 } o_literal { lex: "2026-04-18T16:01:09.256Z" datatype: 1 } } } rows { name { value: "creator" } } rows { quad { p_iri { } o_iri { prefix_id: 14 name_id: 28 } } } rows { name { value: "license" } } rows { prefix { value: "https://creativecommons.org/licenses/by/4.0/" } } rows { quad { p_iri { prefix_id: 7 name_id: 32 } o_iri { prefix_id: 16 name_id: 2 } } } rows { name { value: "introduces" } } rows { quad { p_iri { prefix_id: 6 name_id: 33 } o_iri { prefix_id: 2 name_id: 12 } } } rows { name { value: "wasCreatedAt" } } rows { prefix { id: 8 value: "https://" } } rows { name { value: "platform.sciencelive4all.org" } } rows { quad { p_iri { prefix_id: 6 name_id: 34 } o_iri { prefix_id: 8 } } } rows { quad { p_iri { prefix_id: 10 name_id: 15 } o_literal { lex: "NP created using Declaring a replication study design according to FORRT" } } } rows { prefix { id: 4 value: "https://w3id.org/np/o/ntemplate/" } } rows { name { value: "wasCreatedFromTemplate" } } rows { prefix { id: 3 value: "https://w3id.org/np/" } } rows { name { value: "RAuLEjPp-4dTvPwMkfHggTto1CgjIftiGRAgHlyeEonjQ" } } rows { quad { p_iri { prefix_id: 4 name_id: 36 } o_iri { prefix_id: 3 } } } rows { name { value: "sig" } } rows { name { value: "hasAlgorithm" } } rows { quad { s_iri { prefix_id: 2 } p_iri { prefix_id: 6 } o_literal { lex: "RSA" } } } rows { name { value: "hasPublicKey" } } rows { quad { p_iri { } o_literal { lex: "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" } } } rows { name { value: "hasSignature" } } rows { quad { p_iri { } o_literal { lex: "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" } } } rows { name { value: "hasSignatureTarget" } } rows { quad { p_iri { } o_iri { prefix_id: 1 name_id: 1 } } } rows { name { value: "signedBy" } } rows { quad { p_iri { prefix_id: 6 name_id: 43 } o_iri { prefix_id: 14 name_id: 28 } } }