https://w3id.org/sciencelive/np/RAn_DYEINS9hSmULEWNd8JmdPOykzptJPJCSqiatNLBrA
.trig | .trig.txt | .jelly | .jelly.txt | .jsonld | .jsonld.txt | .nq | .nq.txt | .xml | .xml.txt
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sub:assertion {
sub:decrop-2025-reproduction-outcome a <https://w3id.org/sciencelive/o/terms/FORRT-Replication-Outcome>;
<http://schema.org/endDate> "2026-04-22"^^xsd:date;
<http://www.w3.org/2000/01/rdf-schema#label> "Decrop 2025 phytoplankton CNN metrics reproduced within 0.003 percentage points";
<https://w3id.org/sciencelive/o/terms/hasConclusionDescription> "The independent reproduction confirms the headline classification metrics reported by Decrop et al. 2025. All five reported metrics — top-1 accuracy, top-5 accuracy, micro F1, macro F1, and weighted F1 — match the paper's reported values within 0.003 percentage points. The Decrop 2025 phytoplankton CNN classifier is reproducible end-to-end from the publicly released artefacts (pretrained model, dataset, code package), with no deviations of substance from the original methodology.";
<https://w3id.org/sciencelive/o/terms/hasConfidenceLevel> <https://w3id.org/sciencelive/o/terms/VeryHighConfidence>;
<https://w3id.org/sciencelive/o/terms/hasEvidenceDescription> """Reproduction performed on the 33,718 images of the released test partition using the authors' planktonclas code package and the publicly released EfficientNetV2-B0 weights. Computed metrics versus paper-reported values:
- Top-1 accuracy: 86.3426% (paper: 86.34%; delta +0.003 pp)
- Top-5 accuracy: 98.7633% (paper: 98.76%; delta +0.003 pp)
- Micro F1: 86.3426% (paper: 86.34%; delta +0.003 pp)
- Macro F1: 78.7583% (paper: 78.76%; delta −0.002 pp)
- Weighted F1: 86.2470% (paper: 86.25%; delta −0.003 pp)
All five deltas are below 0.005 percentage points — within the precision the paper itself reports. The full results JSON and predicted probabilities matrix are archived at Zenodo 10.5281/zenodo.19701133. Inference time was approximately 27 minutes for 33,718 images on CPU (Apple M1 Pro). Github repository: https://github.com/annefou/fiesta-decrop-reproduction""";
<https://w3id.org/sciencelive/o/terms/hasLimitationsDescription> "This study reproduces test-set evaluation only; it does not retrain the model. It therefore does not address whether the training procedure itself is reproducible — a future replication that retrains EfficientNetV2-B0 from scratch using the released code and splits would address that. The study also evaluates only on the released test.txt; the model's behaviour on truly out-of-distribution data (other water bodies, other plankton imaging instruments, other taxonomic mixes) is not assessed.";
<https://w3id.org/sciencelive/o/terms/hasOutcomeRepository> <https://doi.org/10.5281/zenodo.19709129>;
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sub:pubinfo {
<https://orcid.org/0000-0002-1784-2920> <http://xmlns.com/foaf/0.1/name> "Anne Fouilloux" .
this: dc:created "2026-04-26T13:58:19.370Z"^^xsd:dateTime;
dc:creator <https://orcid.org/0000-0002-1784-2920>;
dc:license <https://creativecommons.org/licenses/by/4.0/>;
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