Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Antimicrobial Transformation Products in the Aquatic Environment: Global Occurrence, Ecotoxicological Risks, and Potential of Antibiotic Resistance
2023101 citationsBeate I. Escher, Christine Baduel et al.Environmental Science & Technologyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Foon Yin Lai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Foon Yin Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Foon Yin Lai more than expected).
This network shows the impact of papers produced by Foon Yin Lai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Foon Yin Lai. The network helps show where Foon Yin Lai may publish in the future.
Co-authorship network of co-authors of Foon Yin Lai
This figure shows the co-authorship network connecting the top 25 collaborators of Foon Yin Lai.
A scholar is included among the top collaborators of Foon Yin Lai based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Foon Yin Lai. Foon Yin Lai is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Escher, Beate I., et al.. (2023). Antimicrobial Transformation Products in the Aquatic Environment: Global Occurrence, Ecotoxicological Risks, and Potential of Antibiotic Resistance. Environmental Science & Technology. 57(26). 9474–9494.101 indexed citations breakdown →
Wilkins, Chris, Foon Yin Lai, Jake O’Brien, Phong K. Thai, & Jochen F. Mueller. (2018). Comparing methamphetamine, MDMA, cocaine, codeine and methadone use between the Auckland region and four Australian states using wastewater-based epidemiology (WBE).. PubMed. 131(1478). 12–20.5 indexed citations
13.
Prichard, Jeremy, Foon Yin Lai, Phong K. Thai, et al.. (2017). Wastewater analysis of substance use: Implications for law, policy and research. QUT ePrints (Queensland University of Technology). 24(4). 837–849.3 indexed citations
14.
Lai, Foon Yin, Jake O’Brien, Phong K. Thai, et al.. (2016). Cocaine, MDMA and methamphetamine residues in wastewater: Consumption trends (2009–2015) in South East Queensland, Australia. QUT ePrints (Queensland University of Technology).1 indexed citations
15.
Lai, Foon Yin, Phong K. Thai, Christoph Ort, et al.. (2016). Challenges and opportunities in using wastewater analysis to measure drug use in a small prison facility. Figshare.1 indexed citations
Lai, Foon Yin, Jeremy Prichard, Raimondo Bruno, et al.. (2014). Sewage-based epidemiology: a novel, emerging approach to estimating population-level illicit drug consumption. eCite Digital Repository (University of Tasmania).1 indexed citations
Prichard, Jeremy, Christoph Ort, Raimondo Bruno, et al.. (2010). Developing a Method for Site-Specific Wastewater Analysis: Implications for Prisons and Other Agencies with an Interest in Illicit Drug Use. eCite Digital Repository (University of Tasmania).3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.