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 53 · DO #1316 · Archer Vol.3_2_r

Collection
William Andrew Archer (1894–1973) papers
Item/Folder
Volume 3, 1937–1940
Digital Object
DO #1316, page 53
Collection-level dates
1929–1964
Open PDF at page 53 ↗

Page transcription

"Prickly plant; H 471, 1252 (1253)
Eye trouble: i.e. inflammation or swelling - tea from boiled plant as a wash.
Stomach trouble: tea from boiled plant.

Leptotaenia multifida Nutt. "balsam root"; "tosa"(P); "tohsup"(S)
A 5465, B 601
Familiar to all the Indians, and has many medicinal uses, the more common being for coughs and colds, or tuberculosis. For this purpose it is used in various ways: dry the root, cut into small chips and the brew taken as tea. The dried chips may be smoked as cigar-ettes or in pipe, and is sometimes mixed with dried Nicotiana attenuata or other species. Another mixture: equal parts of cedar leaves, old leaves of Artemisia tridentata, old leaves of Chrysothamnus, and root chips of L. multifida, add water to cover and boil. Strain and drink. Also mix root chips with pine pitch, burn on live coals and inhale the fumes.
Some years ago, during an influenza epidemic, a druggist in Carson City sold a commercial preparation of the root.
Sore throat: chew small pieces of dry root as lozenges.
As asthma or bronchial troubles: use powdered root as snuff or smoke chips in cigarette or pipe.
Emetic: when taken as a strong tea, in weaker form is used for tonic.
Smallpox: apply external wash of crushed leaves and roots; pulverized root is powdered and put on sore; also dry root can be boiled and the oil skimmed off the surface of the water.
Trachoma or gonorrheal eyes: put one drop of fresh oil in affected eye.
Swellings: mash root and use as poultice.
Gonorrhea: drink tea from boiled root, either dried or fresh; the fresh root is sometimes combined with fresh root of Rumex hymenosepalus.
Distemper in horses: exercise the horse until he is breathing heavily and then make him inhale fumes from burning root chips.