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 23 · DO #4960 · 183_Cook_Bx1FF4_r

Collection
Cook, Orator Fuller (1867–1949) notes on cotton
Item/Folder
Notes on cotton in Florida, Arizona, Texas, and Mexico, 1916–1929
Digital Object
DO #4960, page 23
Collection-level dates
1912–1929
Open PDF at page 23 ↗

Page transcription

Cotton
(Gossypium. (Generic Char.)
So. Pacific Ry., 10-9-16. p.235

Although the linnaean sexual system of classification of
plants is no longer followed or taught, it still governs very
largely the methods and standpoints of systematic work. Nobody
questions the fact that floral characters are of very great
significance as indicating the relationship of plants, there is
increasing recognition of the fact that the significance of
floral differences is not the same in the different groups of
plants. Some families show great similarity in the forms of
flowers, and others great diversity. There is more and more
of a tendency to recognize the significance of other characters,
particularly that of the fruit, but there seems to be no truly
biological reason why any specialized features of the plant body
should not be taken into account in classification as well as in
the study of plants from other points of view.

The need of using for purposes of diagnosis other differ-
ences than those of the floral parts is greatest, of course, in
cases where the flowers have remained essentially alike, while
other parts have become more specialized. The cultivated cotton
plants and their relatives afford a good example of such a group.
Many of the genera that have been varied have had no general
acceptance among botanists, because little or nothing in the way
of floral differences could be alleged, even in cases where the
plants were radically different in form structure and habits.