Glen Maberly

47 papers receiving 2.3k citations

Hit Papers

An overview of global rice production, supply, trade, and...2014202620182022201420202505007501000

Peers

Glen Maberly
Comparison fields: 5 of 175
  • Endocrinology, Diabetes and Metabolism 780
  • Plant Science 704
  • Pediatrics, Perinatology and Child Health 324
  • Nutrition and Dietetics 238
  • Molecular Biology 224
Replace François Mariotti with:
François Mariotti France
Chaoqiang Jiang China
Benjamin Allès France
Yajun Chen China
Tomoyuki Kawada Japan
Alida Melse‐Boonstra Netherlands
Julie A. Marshall United States
Shosuke Suzuki Japan
S. Dernini Italy
Laura Barrios Spain
Glen Maberly relative to François Mariotti France François Mariotti's profile →
Citations per field
00.5×2.6×
François Mariotti · 1×
Citations per year

Countries citing papers authored by Glen Maberly

Since Specialization
Citations

This map shows the geographic impact of Glen Maberly'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 Glen Maberly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glen Maberly more than expected).

Fields of papers citing papers by Glen Maberly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Glen Maberly. 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 Glen Maberly. The network helps show where Glen Maberly may publish in the future.

Co-authorship network of co-authors of Glen Maberly

This figure shows the co-authorship network connecting the top 25 collaborators of Glen Maberly. A scholar is included among the top collaborators of Glen Maberly 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 Glen Maberly. Glen Maberly is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 5
3 5
4 6
5
Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysisbreakdown →
290
6 13
7 9
8 18
9 27
10 26
11 63
12 289
13 42
14 74
15 45
16 13
17 32
18 8
19 61
20 52

About Glen Maberly

Glen Maberly is a scholar working on Endocrinology, Diabetes and Metabolism, Family Practice and Nephrology, having authored 48 papers that have together received 2.5k indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (20 papers), Diabetes Management and Education (6 papers) and Neonatal Health and Biochemistry (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (780 citations), Applied Psychology (142 citations) and Plant Science (704 citations). Glen Maberly has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Sumithra Muthayya, Jonathan D. Sugimoto, Thomas Astell‐Burt, Xiaoqi Feng, Gideon Meyerowitz‐Katz, Creswell J Eastman, Sumathy Ravi, Leonard Arnolda, Kevin M. Sullivan and Jinkou Zhao. Their work appears in journals such as The Lancet, The Journal of Clinical Endocrinology & Metabolism and American Journal of Public Health.

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.

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