M. Lob

27 papers receiving 343 citations

Peers

M. Lob
Comparison fields: 5 of 73
  • Computational Theory and Mathematics 153
  • Chemical Health and Safety 5
  • Theoretical Computer Science 8
  • Health, Toxicology and Mutagenesis 85
  • Artificial Intelligence 161
Replace S. K. Thomason with:
S. K. Thomason Canada
Akiko Kino Ghana
R. O. Gandy United Kingdom
Wolfram Pohlers Germany
Stanisław Jaśkowski Poland
Clifford Spector United States
Wim Veldman Netherlands
D. J. Shoesmith South Sudan
Piergiorgio Odifreddi Italy
Silvio Valentini Italy
M. Lob relative to S. K. Thomason Canada S. K. Thomason's profile →
Citations per field
00.5×3.3×
S. K. Thomason · 1×
Citations per year

Countries citing papers authored by M. Lob

Since Specialization
Citations

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

Fields of papers citing papers by M. Lob

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside M. Lob, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Lob Line = papers co-authored together M. Lob links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1955127
2 198380
3 197031
4 197621
5 197421
6 197021
7 196218
8
[Risk of asbestosis in workers employed in replacing automobile brake linings].
197314
9 197713
10 19577
11 19686
12 19765
13 19765
14
[Risk of chronic carbon monoxide poisoning in automobile garages. Results of a study in the Lausanne region].
19753
15 19563
16 19532
17 19782
18 19732
19
Chronic Mercury Poisoning in the Luminescent Tube Industry.
19651
20 19721

About M. Lob

M. Lob is a scholar working on Health, Toxicology and Mutagenesis, Computational Theory and Mathematics, Artificial Intelligence, Public Health, Environmental and Occupational Health and Theoretical Computer Science, having authored 35 papers that have together received 392 indexed citations. Recurring topics across this work include History and Theory of Mathematics (4 papers), Logic, programming, and type systems (4 papers), Occupational exposure and asthma (4 papers), Heavy Metal Exposure and Toxicity (4 papers), Computability, Logic, AI Algorithms (3 papers), Air Quality and Health Impacts (3 papers), Logic, Reasoning, and Knowledge (3 papers) and Analytic Number Theory Research (2 papers). The work is most often cited by research in Computational Theory and Mathematics (153 citations), Chemical Health and Safety (5 citations), Theoretical Computer Science (8 citations), Health, Toxicology and Mutagenesis (85 citations) and Artificial Intelligence (161 citations). M. Lob has collaborated with scholars based in Switzerland, United Kingdom and France. Frequent co-authors include Stanley S. Wainer, Michel Guillemin, M. Bérode, Y. de Ribaupierre, Pascal Bovet, P. O. Droz and Edouard Haller. Their work appears in journals such as Journal of Symbolic Logic, International Archives of Occupational and Environmental Health, Occupational and Environmental Medicine, Archive for Mathematical Logic and Lecture notes in mathematics.

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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