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/RAhYEwAvbxK6q2V4nTOSrIgykEXGL_iL3a0F_8v_ElLtg/> .
@prefix this: <https://w3id.org/sciencelive/np/RAhYEwAvbxK6q2V4nTOSrIgykEXGL_iL3a0F_8v_ElLtg> .
@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/Proposed%20models%20to%20determine%20Section%20Condition%20Rating%20%28SCR%29%20based%20on%20the%20damage%20count%20and%20weighted%20damage%20count%20approaches%20were%20able%20to%20predict%20Mean%20Panel%20Rating%20%28MPR%29%20with%20an%20R2%20value%20of%200.93.> 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 "2026-03-13T14:12:15.000Z"^^xsd:dateTime ;
    dcterms:creator <https://w3id.org/np/RALe_3U-0OKr-rc5FzaSc7xw1nPuGq1LkWoncmx6DXAV4/ai-mistral-ji> ;
    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/Proposed%20models%20to%20determine%20Section%20Condition%20Rating%20%28SCR%29%20based%20on%20the%20damage%20count%20and%20weighted%20damage%20count%20approaches%20were%20able%20to%20predict%20Mean%20Panel%20Rating%20%28MPR%29%20with%20an%20R2%20value%20of%200.93.> ;
    npx:wasCreatedAt <https://platform.sciencelive4all.org> ;
    rdfs:label "AIDA sentence: Proposed models to determine Section Condition Rating (SCR) based on the damage count and weighted damage count approaches were able to predict Mean Panel Rating (MPR) with an R2 value of 0.93." ;
    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> .
}