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 42 · 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 42
Collection-level dates
1948–1977
Open PDF at page 42 ↗

Page transcription

when I was first beginning these studies, and I told a man who is now deceased,
(his name shall not, therefore, be brought before you because it isn't fair to
him, since he is dead and cannot talk back) I said, "I want to study classification
of Manihot esculenta." He said, "Your nuts, your absolutely nuts, you can't do
anything with the classification of that bunch of things, particularly a cultivated
plant." He couldn't have done a better job to set me on course by waving that kind
of flag in my face. But if you stop to think how you are going to study these groups
of plants such that you can make some sort of a reasonable classification of them,
you soon learn of the great difficulties, because the variations between plants
is so slack from one plant to the next that you have a great deal of difficulty in
recalling the total variation that one plant has in relation to the next plant, and
then by the time you have gotten through the second, third, or fourth, or fifth, or
maybe the hundredth plant, you have forgotten entirely what the content of variation
was in the first plant. So to try to make these comparisons, you are in great need
of some sort of extension of your arm in order to get into this kind of study. A
very factual problem generated some of the ideas which will be going into this
course. Along with these ideas the questions of in taxonomy itself that were
hallowed words, hallowed ideas, and so forth bugged me for a long time. It seemed
when I first got to be a student in taxonomy that the professor somehow knew what
a species was, because the professors were guys that were generating new species,
they were naming ;new species all the time, and I always wanted to know, "how in
the name of did you know that this thing was a new species, different from
anything else that is presently . But I discovered very quickly that
some of the professors were quite honest in saying, "Well, I don't know what this
new species is, and I don't know whether this thing here is a new species, all I
know is that in my study of the groups of organisms I haven't seen anything that
looks quite like it. Therefore, it is a new species." How do you grab that definition then? How could you give that to a student and expect that he is