Empirically calibrated simulations reveal the limits of phenotypic clustering algorithms for biodiversity assessment in data-scarce crops.

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Last updated 8/26/2026, 9:54:01 PM

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African DSI DataBank. Empirically calibrated simulations reveal the limits of phenotypic clustering algorithms for biodiversity assessment in data-scarce crops.. AFDSI-PUB-172. 2026. https://hub.africandsidatabank.africa/cite/AFDSI-PUB-172 Mirrored from data source: PubMed: https://pubmed.ncbi.nlm.nih.gov/41406127/.Copy citation

@misc{AFDSIPUB172,
  title        = {Empirically calibrated simulations reveal the limits of phenotypic clustering algorithms for biodiversity assessment in data-scarce crops.},
  author       = {{African DSI DataBank}},
  year         = {2026},
  howpublished = {\url{https://hub.africandsidatabank.africa/cite/AFDSI-PUB-172}},
  note         = {African DSI DataBank citable identifier AFDSI-PUB-172; Mirrored from data source: PubMed: https://pubmed.ncbi.nlm.nih.gov/41406127/}
}

AFDSI-PUB-172 is a stable, resolvable local identifier — not a registered DOI. See Terms of use's "Citation policy" for the full explanation.