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 133 · DO #404 · 204_Popenoe_Bx30aFF5r

Collection
Wilson Popenoe (1892–1975) family papers
Item/Folder
Cinchona manuscript - correspondence, 10 January 1940–6 August 1942
Digital Object
DO #404, page 133
Collection-level dates
1882–1975
Open PDF at page 133 ↗

Page transcription

Antigua, 20 Nov 1941

Mr Rosengarten:

Consideration of the grafting problem, it seems to me, must taken into account the following factors and possible a few others with which we are not yet familiar:

1. Other things being equal, some varieties or clones will give a much higher percentage of "takes" or successes than other varieties. We may find that this ranges from as low as 30 or 40% with varieties which are hard to graft, to 90% with those which are easy to graft. This is in line with horticultural experience with many other tree crops.

2. To obtain a high percentage of successes in grafting, cion wood must be as nearly ideal as possible. This means that the wood must be of the proper stage of ripeness; it must not be flowering wood; and it must be of the right diameter. I doubt that we are qualified, as yet, to choose ideal wood; but we know something about it and will know more with time. In much of the grafting work done to date, operators have used wood which they knew was not satisfactory, solely because we were anxious to propagate the clones just as rapidly as possible. Percentage of success have therefore been, in certain cases, lower than necessary.

3. Stock plants must be in prime condition; that is, they must be of the right stem-diameter, and in vigorous growth. If on unsuitable soil they can never be in prime condition; and if taken when too young or too old maximum success can not be attained. This also has been a factor in the past, when we have not always had an abundance of stock plants with which to work.

4. Weather conditions. With all nursery work there is a