Featured BIOSPEX Project
How Weird is That?


How Weird is That? logo

Contact

Mikayla Buckley

Organization

Florida State University

Description

This project will help create data sets to train and test a machine learning algorithm that will detect anomalies in specimen data

How Weird is That? is training machines to recognize the language that researchers use to describe anomalies in the natural world (e.g., “in my experience it’s odd to see this species so far north”) and differentiate it from less alarming word uses (e.g., “the population consistently had an odd-number of segments”).  Public participants are differentiating between these two cases and describing the abnormal feature as falling into one of several categories (e.g., the first example is a distributional anomaly).  This enables earlier flagging of biological outliers to get the information to the right stakeholders faster.  These oddities can mark the early stages of transformative change (e.g., an invasive species’ arrival), so faster information hand-offs are way better!  The lead researcher on this project is an undergraduate student finishing her Honors Thesis in Computational Biology.

Expeditions

3 Expeditions 50412 Digitizations 1589 Participants

Title Date

No Expeditions exist.

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How Weird's Early, Earlier, Earliest

Analyzing the use of the words "early", "earlier", and "earliest" to describe phenological anomalies in specimen records

5997 Digitizations

100.00% Completed


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How Weird's Late, Later, Latest

Analyzing the use of the words "late", "later", and "latest" to describe phenological anomalies in specimen records

19734 Digitizations

98.67% Completed


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How Weird's Abnormal, Odd, Unusual, Weird, Than

Analyzing the use of the words "abnormal", "odd", "unusual", "weird", and "than" to describe anomalies in specimen records

24681 Digitizations

98.29% Completed


Events


Title Date

No Events exist.

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No Events exist.

Digitizations


Heat Map Digitized Specimens


FSU Florida Museum IdigBio University of Florida National Science Foundation