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 28 · DO #4718 · 231_Rogers_Bx4FF9_r

Collection
David James Rogers (1918–2007) papers
Item/Folder
Intl. Nat. Conf. on Systematic Bio. , 1967
Digital Object
DO #4718, page 28
Collection-level dates
1948–1977
Open PDF at page 28 ↗

Page transcription

THE CONSTRUCTION OF A CLASSIFICATION

W. H. Wagner, Jr.

Botanical Gardens
The University of Michigan

How are most classifications actually constructed? In the vast majority of cases, we simply inherit past classifications and modify them, adding here, subtracting there. Classifications were originally constructed on the basis of a few conspicuous characters, and were gradually changed by successive workers. Most active taxonomists are really not much concerned with the theory and philosophy behind the construction of classification; they merely do their work and hope for the best. Most workers who have dealt with the problems have usually had some special "iron in the fire" - expressing phenetic relationships, expressing fossil records, and so on. Nevertheless, the problems of constructing classifications are very serious ones, and of importance to biology. Any value that the present discussion may have lies in its attempt to see the whole picture: What are the problems? What, if anything, can or should be done about them?

We are confronted with a series of dilemmas, and the past dozen or so years have produced a great deal of argument, especially in the pages of such journals as Systematic Zoology and Taxon. What is homology? How can characters be quantified, if at all? Should characters be considered equal in significance, or should they be weighted? We cannot delve into these problems in detail, of course - the problems of actual construction of a classification are by themselves nearly overwhelming.

The rationale or concept which underlies the system determines its ultimate form. Early classifications aimed mainly at identification - either to categorize organisms according to their usages, or for pigeon-holing purposes. A latter-day variation is the goal of purely phenetic classification or assortment only, based upon all available data, all characters counted as equal in importance. Modern "biological" classifications, on the contrary, emphasize evolution. Concepts of primitiveness and specialization play a role, and some characters are more important than others in showing relationships. Even evolutionary taxonomists are not agreed, however, on whether the classification should express levels or lines. This is a special problem for plants, where parallelism and convergence have yielded pteridophytes, gymnosperms and angiosperms. Another question has to do with whether the chronology of the evolutionary branchings should be considered or not in setting up taxonomic categories.

By far the greatest problem in constructing classifications has to do with application of categories. Hierarchial inflation has made many systems unwieldy and difficult to use, where species-groups have been raised to genera, genera to families, families to orders, and so on. The problem of the evolutionary continuum enters here, because much of categorization is based upon gaps in the record. The year-by-year changes in classification systems have discouraged many biological workers, especially those in applied fields, about taxonomy, and the fact is that the instability of taxonomy is its chief drawback.