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 14 · DO #4626 · 231_Rogers_Bx1FF20_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Correspondence "Reader's File", October–December 1969
Digital Object
DO #4626, page 14
Collection-level dates
1948–1977
Open PDF at page 14 ↗

Page transcription

Critique of "A Numerical Taxonomic Study of
The Mexican Species of Solanum, section Tuberarium"

1. Has the material been published previously in the same or similar form?
Studies on Solanum, using some sort of statistical technique have been
published before, (Heiser, et. al., 1965) and, there have been many "objective"
comparisons on other groups made between the statistical methods and some
"classical" classification, and most are invalid, for the following reasons.
(1) The statistical methods are based upon some assumptions which may or may not be
valid, and these assumptions are quite different from the assumptions expressed
or inherent in the classical methods. (2) The authors do not state the bases for
accepting one or the other statistical package, and leave the reader to guess why
they chose the ones they did. (3) There is no effort to explain (if they indeed can)
whether the mathematical bases underlying the statistical assumptions are satisf-
actory for the purposes of taxonomy.

2. Has the research been carried far enough to warrant publication?
Clearly, it has not. There are no clear-cut decisions as to the arrangement,
or re-arrangement of the taxa included in the section, and this is the only basis
for publication of some work in BRITTONIA. We are left at the end with no decision
which method of numerical taxonomy is valid, if any, nor why there are differences
in the output. If the information of the species taken from cultivated specimens
differs from the information on the wild-grown plants, we clearly deserve to have
these differences reconciled. Why, one asks, were not both sets of data run
together?

The authors do not seem aware that, having used nearly 50% of the information
on leaf characters, they have heavily weighted the classifications toward the
vegetative information about the plants. This, in itself, could help to explain why
their various results do not agree with the earlier classifications where I am
sure the authors considered reproductive or chromosomal differences uppermost.
Furthermore, in nearly every case of the measurement characters, they have duplicated
the character in such a way that they have introduced false biological weighting.
It is not conceivable that there are that many independent genetic systems at work
in determining leaf dimensions, and if our classifications, numerical or otherwise,
do not make some effort to reflect genetic variation in the plants under study,
we have no reason for calling ourselves taxonomists. However, if the authors had
clearly stated at the outset that their objectives were to build a classification
predominantly on information from the leaves, then they may proceed, and all will
understand them.

3. Is BRITTONIA the most suitable journal for the publication of this
material?
No, nor any other, considering the present state of the work.