Method / resourcemodel-written summary

The four reported prediction errors were 4.598, 8.657, 0.4586 and 5.106, but the abstract garbles their constituent mapping.

A claim from [Quantitative prediction of active constituents in rhubarb by near infrared spectroscopy and radial basis function neural networks]. · 2007

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The four reported prediction errors were 4.598, 8.657, 0.4586 and 5.106, but the abstract garbles their constituent mapping.

Outcome
RMSEPse1
Value
4.598, 8.657, 0.4586, and 5.106e1

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Rheum rhabarbarum
Rheum rhabarbarum · TaxonDieter Weber ( User:Uellue ) · CC BY-SA 3.0 · Wikimedia Commons ↗

Schema note from the model: Constituent mapping is unclear due to missing words.

Verbatim

e0

“Near infrared spectroscopy (NIRS) and artificial neural networks were used for the quantitative prediction of four active constituents in rhubarb”

✓ located verbatim in the source · abstract, characters 0–145
e1

“RMSEPs for the were 4.598, 8.657, 0.4586, and 5.106, respectively”

✓ located verbatim in the source · abstract, characters 593–658

Title

[Quantitative prediction of active constituents in rhubarb by near infrared spectroscopy and radial basis function neural networks].

Xiao-hui Yu; Zhuo-yong Zhang; Qun Ma; et al. PubMed 2007

Other claims from this paper (5)

Record rev-99a9405fcdb88f3f4d1b6952ad186cbe620dfd67ca858329c09baa5c1d058160 · schema claims-v0.9 · position 5 in the model’s answer