@prefix this: <https://w3id.org/sciencelive/np/RAQbvusYubgaYlU7YEPIgPmTwqDoylwiq5FKyrVgF95qM> .
@prefix sub: <https://w3id.org/sciencelive/np/RAQbvusYubgaYlU7YEPIgPmTwqDoylwiq5FKyrVgF95qM/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix dc: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

sub:Head {
  this: a np:Nanopublication;
    np:hasAssertion sub:assertion;
    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo .
}

sub:assertion {
  sub:phytoplankton-claim a <https://w3id.org/sciencelive/o/terms/FORRT-Claim>, <https://w3id.org/sciencelive/o/terms/model_performance-FORRT-Claim>;
    dc:source <https://doi.org/10.3389/fmars.2025.1699781>;
    <http://www.w3.org/2000/01/rdf-schema#label> "Phytoplankton CNN classification across 95 classes";
    <https://w3id.org/sciencelive/o/terms/asAidaStatement> <http://purl.org/aida/A%20convolutional%20neural%20network%20identifies%20phytoplankton%20taxa%20across%2095%20classes%20with%2086.3%25%20top-1%20accuracy%20and%2098.8%25%20top-5%20accuracy.> .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://orcid.org/0000-0002-1784-2920> .
}

sub:pubinfo {
  <https://orcid.org/0000-0002-1784-2920> <http://xmlns.com/foaf/0.1/name> "Anne Fouilloux" .
  
  this: dc:created "2026-04-26T13:41:39.130Z"^^xsd:dateTime;
    dc:creator <https://orcid.org/0000-0002-1784-2920>;
    dc:license <https://creativecommons.org/licenses/by/4.0/>;
    npx:introduces sub:phytoplankton-claim;
    npx:wasCreatedAt <https://platform.sciencelive4all.org>;
    <http://www.w3.org/2000/01/rdf-schema#label> "NP created using Declaring an original claim according to FORRT";
    <https://w3id.org/np/o/ntemplate/wasCreatedFromTemplate> <https://w3id.org/np/RAZWyM8D16ya3S1zhCvrG1f0iSpd9-8onVWp0FTvvX7LQ> .
  
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