We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
0
Article
?
AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button.
Tier 2
?
Original research — experimental, observational, or case-control study. Direct primary evidence.
Environmental Sources
Marine & Wildlife
Remediation
Sign in to save
Intersections between materials science and marine plastics to address environmental degradation drivers: a machine learning approach
Environmental Science Advances
2023
1 citation
?
Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Score: 30
?
0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Henrique de Medeiros Back,
Henrique de Medeiros Back,
Daphiny Pottmaier,
Camilla Kneubl Andreusi,
Camilla Kneubl Andreusi,
Orestes Estevam Alarcon
Daphiny Pottmaier,
Orestes Estevam Alarcon
Orestes Estevam Alarcon
Summary
Using natural language processing and expert knowledge, this study connected the marine plastics research community with polymer science to better understand why plastics degrade in the ocean. The machine learning approach identified shared concepts between fields that could accelerate solutions to marine plastic pollution.
This article uses natural language processing and expert knowledge to bridge the marine plastics community to polymer science.
Sign in to start a discussion.