Find related topics. | Discover entities. | See connections. | Build a topical map.
Building topical map: Starting…
Marsh test: Applications & Standards
The Marsh test is a highly sensitive method in the detection of arsenic, especially useful in the field of forensic toxicology when arsenic was used as a poison. It was developed by the chemist James Marsh and first published in 1836. The method continued to be used, with improvements, in forensic toxicology until the 1970s.
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
More settings
Marsh test topic overview
The analysis highlights Applications and Standards as prominent areas in the source structure around Marsh test.
Related topics
44
Source areas
6
Connected nodes
50
Extracted relationships
105
Concept neighborhoods
20
Bridge connections
50
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Precursor methods · 14 topics
In fiction · 9 topics
Circumstances and methodology · 8 topics
Overview · 7 topics
First notable application · 5 topics
Specific reactions involved · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Marsh test connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Marsh test shows recurring relationship patterns in the source. For example, Marsh test → Addenda, Agustí, American Chemical Society, Angewandte Chemie, Annalen, Arsenic, Arsenik, Arsennachweis, Bertomeu-Sánchez, Beschreibung, Bibcode, Britain, Campbell, Chemie, Chemistry, Crime, Criminal, England, Excess Potential, First Paper Another extracted example is Marsh test → An Introduction, Arsenic, Blakiston's Son, Chemical Pharmacology, Co, Hugh, James Alfred, James Marsh Test, Kegan Paul, London, Ltd, McMuigan, Philadelphia, Retrieved, Trench, Trübner, Wanklyn. Use these groups to spot repeated connection types before inspecting the individual relationships.
Marsh test
Top relations
related to Further reading· 54
Marsh test → Addenda, Agustí, American Chemical Society, Angewandte Chemie, Annalen, Arsenic, Arsenik, Arsennachweis, Bertomeu-Sánchez, Beschreibung, Bibcode, Britain, Campbell, Chemie, Chemistry, Crime, Criminal, England, Excess Potential, First Paper
related to External links· 17
Marsh test → An Introduction, Arsenic, Blakiston's Son, Chemical Pharmacology, Co, Hugh, James Alfred, James Marsh Test, Kegan Paul, London, Ltd, McMuigan, Philadelphia, Retrieved, Trench, Trübner, Wanklyn
related to First notable application· 15
Marsh test → Although, As, Charles Lafarge, France, He, In, Lafarge, Lafarge's, Marie, Marie Lafarge, Marsh, Mathieu Orfila, Orfila, The, Tulle
has effect· 7
Marsh test → Lafarge, Lafarge's, Marsh, Mme, The, The French, The Lafarge
related to In fiction· 6
Marsh test → Bill Bergson Lives Dangerously, Bunter, Lord Peter Wimsey’s, Marsh, Marsh’s, Strong Poison
related to Specific reactions involved· 5
Marsh test → As3, Even, Here, The Marsh, They
is a· 1
Marsh test → highly sensitive method in the detection of arsenic
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Marsh test relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 105 structured relationships around Marsh test. Examples in this analysis include Marsh test → is a → highly sensitive method in the detection of arsenic and Marsh test → has effect → The Lafarge. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Marsh test
is a
highly sensitive method in the detection of arsenic
0.90
text
Marsh test
has effect
The Lafarge
0.60
section
Marsh test
has effect
Mme
0.60
section
Marsh test
has effect
Lafarge's
0.60
section
Marsh test
has effect
Marsh
0.60
section
Marsh test
has effect
The French
0.60
section
Marsh test
has effect
Lafarge
0.60
section
Marsh test
has effect
The
0.60
section
Marsh test
related to External links
McMuigan
0.60
section
Marsh test
related to External links
Hugh
0.60
section
Marsh test
related to External links
An Introduction
0.60
section
Marsh test
related to External links
Chemical Pharmacology
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Marsh test bring nearby vocabulary together. In this analysis, examples include Test, Arsenic and James. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Marsh test
Test
Arsenic
James
Poison
Used
Case
First
Poisoning
Although
Forensic
Toxicology
Could
marsh test
Test
Arsenic
Poison
Used
James
Poisoning
Although
Case
First
Forensic
Form
Toxicology
arsenic
Test
Marsh
Poison
Would
Poisoning
Present
Used
Body
Could
Trioxide
Gas
First
james marsh
Test
Arsenic
James
Marsh
Poison
Used
Case
First
Poisoning
Although
Forensic
Toxicology
arsenic trioxide
Test
Marsh
Poison
Would
Poisoning
Present
Could
Zinc
Used
Body
Trioxide
Gas
arsenic poisoning
Test
Marsh
Victim
Arsine
Poison
Case
Gas
Would
Poisoning
Used
Present
France
nitric acid
Arsine
Zinc
Gas
Would
Hydrogen
Presence
First
Poisoning
France
Detection
Form
Poisoned
hydrochloric acid
Arsine
Zinc
Gas
Would
Hydrogen
Presence
First
Poisoning
France
Detection
Form
Poisoned
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Marsh test, one of the stronger structural bridges in this analysis connects Marsh test with Precursor methods. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
Marsh test — Precursor methods· splits 36 ⟂ 15Marsh test — In fiction· splits 41 ⟂ 10Marsh test — Circumstances and methodology· splits 42 ⟂ 9Marsh test — Overview· splits 43 ⟂ 8Marsh test — First notable application· splits 45 ⟂ 6
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Marsh test
Nodes51
Edges50
Triples105
Avg. degree1.96
Density0.039216
Components1
Source & methodology
TTTA analyzes the structure around Marsh test to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Applications & Standards, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
