HMM Metrics in Pesticide Exposure Detection Task.

<div><p>Pollinator populations are declining globally at an unprecedented rate, driven by factors such as pathogens, habitat loss, climate change, and the widespread application of pesticides. Although colony losses remain difficult to prevent, precision beekeeping has introduced non-inv...

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Bibliographic Details
Main Author:	Alex Otesbelgue (5488982) (author)
Other Authors:	Amara Jean Orth (21567548) (author), Chandler David Fong (21567551) (author), Carol Anne Fassbinder-Orth (21567554) (author), Betina Blochtein (715503) (author), Maria João Ramos Pereira (7866134) (author)
Published:	2025
Subjects:	Biotechnology Ecology Science Policy Infectious Diseases Biological Sciences not elsewhere classified Information Systems not elsewhere classified tetragonisca fiebrigi </ provide initial evidence offers significant economic native pantropical pollinators methodologies remain underexplored machine learning techniques hidden markov model commonly used insecticide identify stress responses lethal pesticide exposure stingless bee bioacoustics keeping stingless bees div >< p analyze acoustic data detecting pesticide exposure prevent hive losses monitoring hive conditions stingless bees stingless bee acoustic monitoring acoustic data unexposed conditions related stress detecting stressors pesticide toxicity hive identification widespread application unprecedented rate study addresses specific events residual concentrations proven effective precision beekeeping pollinator populations particularly susceptible matlab ’ invasive tool invasive strategies honeybee colonies habitat loss findings advance declining globally critical need conservation benefits climate change
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HMM Metrics in Pesticide Exposure Detection Task.

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