Author

Raphael LaFrance

Florida Museum of Natural History

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 2 Approach:machine learning (classical)· 2 Organism:plant (other)· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:ecology & biodiversity· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Robert GuralnickiD· 3 shared Daijiang LiiD· 1 shared Douglas E. SoltisiD· 1 shared Ellen G. DennyiD· 1 shared Erin L. GradyiD· 1 shared John DeckiD· 1 shared Julie M. AlleniD· 1 shared Michael DenslowiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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Curved chords = mutual co-authorship

3 shared papersEcology

Robert GuralnickORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Petal to the metal: The slow road to automating large-scale phenology labeling for herbarium specimens

Erin L. Grady, Raphael LaFrance, Daijiang Li, Russell Dinnage, Ellen G. Denny, John Deck, Robert Guralnick

The paper presents a machine learning pipeline for automating flower detection on herbarium specimens, resulting in 11.1 million labeled records but highlighting the need for full metadata digitization.

Applications in Plant Sciences · Oct 1, 2026Peer-reviewedEcology

Regional trait-threat interactions determine extinction risk in plants.

Zoe Dennehy-Carr, Raphael LaFrance, Douglas E. Soltis, Pamela Sue Soltis, Robert Guralnick

The paper assesses how plant functional traits interact with regional threats to predict extinction risk, finding smaller herbaceous species are more vulnerable and some threats reduce extinction risk.

bioRxiv · Jul 17, 2026 · PreprintEcology

Ensemble automated approaches for producing high quality herbarium digital records

Robert Guralnick, Raphael LaFrance, Julie M. Allen, Michael Denslow

The paper develops an ensemble method combining rule-based and large language model approaches to improve the accuracy of converting OCR text from herbarium labels into standardized digital data records.

Applications in Plant Sciences · Nov 5, 2024Peer-reviewedBioinformatics