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NOCAIR/phyto_class_ucsc_updated
phyto_class_ucsc_updated is a machine learning model from NOCAIR. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-sa-4.0.
This model and readme file are derivative of the phytoClassUCSC classifier.
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Updated Mar 24, 2025
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From the Hugging Face model README
This model and readme file are derivative of the phytoClassUCSC classifier.
This model was designed and trained to work with IFCB data generated in Monterey Bay. While that does not mean it may not perform well in other locations, the distribution of training images reflects common phytoplankton observed at the Santa Cruz Wharf and Power Buoy locations. Independent model validation should be used when applying the model to other sites.
Generalized micro-phytoplankton classifier for common taxa found in the Monterey Bay.
Researchers intersted in a general.
Observing and identifying rare or non-endemic taxa.
Model classes were chosen based on common and resolvable phytoplankton taxa. Taxonomic groupings were chosen based on what researchers in the lab felt groups that could be confidently identified, given the expertise and research intersts of the lab.
Model was trained on images from Imaging FlowCytobot (IFCB) instruments primary deployed at the Santa Cruz Wharf and the Monterey Bay Aquarium Research Institute (MBARI) Power Buoy. The Santa Cruz Wharf IFCB (#104) is an early generation
Deployed model performance will vary with the natural variabilability in the observed phytoplankton communities over different time scales (seasonality). As such model performance should be evaluated throughout IFCb deployments using independently labled images.
Training model performace was evaluated using a held-back validation training set. F1-scores were calcuated for each class. See Results here
Uncertainty is addressed by applying a set of class-specific thresholds for each prediction. This works reasonably well for out-of-distribution images.
To Be Described
None
This model was developed as in interation of previous classification efforts and as such is subject to a history of decision making that is not captured here. For that reasons this classifier is not a panacea for all phytoplankton image data, but was specifically developed for looking at phytoplankton communities in Monterey Bay.
IFCB collected data are very context specific and subject to both observation configurations and small-scale variability.
Review section 4.9 of the model cards paper.