Hunt Institute for Botanical Documentation
A Research Division of Carnegie Mellon University

Hunt Institute Archives Text Discovery Platform

Search a large and growing portion of our online collections, including handwritten documents.
PROTOTYPE

This prototype uses state-of-the-art artificial intelligence, including a vision-language model (VLM) capable of reading handwritten documents as well as typed and printed text, to create searchable transcriptions of digitized materials in the Hunt Institute Archives. This makes it possible to search the textual contents of individual pages, including material that may not be described in the archival catalog.

Use Keyword search for specific words, names, dates, scientific names, or phrases. Try Semantic search (experimental) to describe a topic, question, or kind of material when you do not know the exact wording used in the documents.

About the AI-generated transcriptions

The transcriptions are generated automatically from page images and may contain errors, especially with difficult handwriting, unusual names, multiple languages, image-quality problems, or complex layouts. They are intended primarily as a discovery aid rather than authoritative transcriptions.

Each result provides the generated transcription and links to the original digitized material and associated archival description so that readings can be checked against the source. The transcription workflow uses AI models run locally by the Hunt Institute.

About Keyword and Semantic search

Keyword search is the default and matches the wording in the transcriptions. Results contain all your terms. Use quotes for an exact phrase. Substring matching is supported, so aceae can find plant-family names ending in -aceae.

Semantic search (experimental) is useful when you know what kind of material you are looking for but do not know the words used in the documents. It ranks transcribed passages by similarity of meaning, so relevant results may not contain the exact words in your query.

Semantic queries can be broad research topics, descriptions of activities or relationships, or natural-language questions. For example:

Semantic search is not a chatbot: a question is used as a search query, and the system returns archival passages that appear conceptually related to it rather than generating an answer or summary. Short descriptions and ordinary research questions generally work better than lists of disconnected keywords. Quotation marks have no special meaning in Semantic mode. Cross-language matching may work in some cases, but it should not be treated as translation.

Keyword and Semantic search are complementary. Keyword search lets you require particular wording; Semantic search can surface differently worded passages about the same subject. Depending on the research question, trying both can reveal different useful material.

Open a result: use the prominent page-and-transcription link to see the metadata, PDF, and full transcription. Keyword-search terms are highlighted in the transcription.

Archives Collections Database (ArchivesSpace): the Collection, Item/Folder, and Digital Object links open the corresponding archival records. Collection-level dates describe the collection as a whole, not necessarily the specific item or page.

If a PDF does not load: on the detail page, use the Digital Object link, click “Go to file” in ArchivesSpace, and navigate to the page number shown here.

Current limitations
  • Automated transcriptions can contain missing or incorrect text or unintended repetition. Difficult handwriting, image quality, unusual layouts, and multiple languages can reduce accuracy. Always consult the original page image when an exact reading matters.
  • Semantic search remains experimental. Its rankings are an additional discovery aid, not a complete or definitive set of relevant results, and highly ranked pages can sometimes be only broadly related.
  • This is an active prototype. Search coverage, transcriptions, functionality, and the interface may continue to change as additional archival material is processed and the system is improved.

← Back to results

Page 180 · DO #4666 · 231_Rogers_Bx2FF27_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Taximetrics Course - Student Reports, 1966–1968
Digital Object
DO #4666, page 180
Collection-level dates
1948–1977
Open PDF at page 180 ↗

Page transcription

page 5

physiology of a certain phenomenon going on for one species, and there are 100
species in this genus so something like that we don't have any information in
regard to the other 99 so it is not comparable information. But we keep that in
the back of our minds and we can perhaps whether justifiably or unjustifiably
infer that maybe the others are the same. (Student) I think to go out on a
limb and say that seeds tell me that plant distribution is valid as a key to
the identification plant. (Henry) It is, but we are not talking about identi-
fication, we are talking about classification now. And it is real handy to know
that a certain group of plants only exist in Australia. It limits our searching.
We can use that definitely in a key for identification. (Student) But doesn't
this fact that they are located only in one place imply that they differ from
other plants in some marked way? (Henry) It does imply that. Well, we infer
that as true. On some occasions we can take two quite different plants and bring
them down to the low lands and may in the Arctic conditions and let
us say that we can grow them under arctic or alpine conditions. Both of those
plants may become cushion or dwarf plants, quite different than they are in the
low lands, but both of them will react the same way, and I am sure that Craig
here can give you a number of examples of that sort of situation on the
They are reacting to their environment. And if you are doing an ecological
classification, then such characters are of importance to you.

Host determination variation, that is primarily one that mycologists get
into in particular. And again that is a very good identification procedure,
but it is not necessarily valid, unless you can have other information if
it is a segregating information, then you may be able to use it. But in general,
host variation is not important. It is nice that we find that a certain genus of
fungi is always on a particular type of plant. It is real helpful for identifica-
tion purposes, but it is not how we cluster them. It is not how we determine
whether they are a nameable species unit. We also have another type of variation
which I have down here as density. Sometimes plants that grow in great masses