Nanopublications

@prefix cito: <http://purl.org/spar/cito/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix hycl: <http://purl.org/petapico/o/hycl#> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix npx: <http://purl.org/nanopub/x/> .
@prefix nt: <https://w3id.org/np/o/ntemplate/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix sub: <https://w3id.org/sciencelive/np/RAVL2dPYGvTEdLItK-NV5zzUqYA8enIA_1ERxfgBWmC3w/> .
@prefix this: <https://w3id.org/sciencelive/np/RAVL2dPYGvTEdLItK-NV5zzUqYA8enIA_1ERxfgBWmC3w> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

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

sub:assertion {
<http://purl.org/aida/Both%20damage%20count%20and%20weighted%20damage%20count%20approaches%20were%20able%20to%20predict%20correct%20condition%20category%20for%2086%25%20%2831%20out%20of%2036%20sections%29%20of%20the%20cases.> cito:obtainsSupportFrom <https://doi.org/10.1007/s42947-025-00603-7> , <https://doi.org/10.18710/EHMQU7> ;
a hycl:AIDA-Sentence .
}

sub:provenance {
sub:assertion prov:wasAttributedTo <https://w3id.org/np/RALe_3U-0OKr-rc5FzaSc7xw1nPuGq1LkWoncmx6DXAV4/ai-mistral-ji> .
}

sub:pubinfo {
  <https://w3id.org/np/RALe_3U-0OKr-rc5FzaSc7xw1nPuGq1LkWoncmx6DXAV4/ai-mistral-ji> foaf:name "ai-mistral-ji" .
  this: dcterms:created "2026-03-13T14:12:18.000Z"^^xsd:dateTime ;
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    dcterms:license <https://creativecommons.org/licenses/by/4.0/> ;
    npx:hasNanopubType hycl:AIDA-Sentence , <http://purl.org/petapico/o/hycl> ;
    npx:introduces <http://purl.org/aida/Both%20damage%20count%20and%20weighted%20damage%20count%20approaches%20were%20able%20to%20predict%20correct%20condition%20category%20for%2086%25%20%2831%20out%20of%2036%20sections%29%20of%20the%20cases.> ;
    npx:wasCreatedAt <https://platform.sciencelive4all.org> ;
    rdfs:label "AIDA sentence: Both damage count and weighted damage count approaches were able to predict correct condition category for 86% (31 out of 36 sections) of the cases." ;
    nt:wasCreatedFromTemplate <https://w3id.org/np/RALmXhDw3rHcMveTgbv8VtWxijUHwnSqhCmtJFIPKWVaA> .
  sub:sig npx:hasAlgorithm "RSA" ;
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    npx:hasSignatureTarget this: ;
    npx:signedBy <https://w3id.org/np/RALe_3U-0OKr-rc5FzaSc7xw1nPuGq1LkWoncmx6DXAV4/ai-mistral-ji> .
}