Bibliographic record
Abstract
The authoritative guide to American English as it's really used today. The Cambridge Dictionary of American English CD-ROM contains the full text of the printed dictionary, as well as spoken pronunciations for every word in the text to the entry where that word is defined; tools that allow users to add their own notes to the dictionary; and sophisticated lookup tools that let learners search by grammar code, part of speech, and usage label as well as by word. The CD-ROM can also be linked with Microsoft(r) Word to allow fast lookups from word processing documents. Based on the Cambridge International Corpus, a database that includes more than 200 million words of spoken and written American English, the paperback edition contains more than 40,000 definitions of words and phrases. Entries are organized by meaning, and words with more than one meaning are clearly marked with a boxed guideword, so there's no guesswork involved in finding the right entry. Definitions are written using a carefully controlled 2,000-word defining vocabulary, so they are clear and easy to understand. Authentic, full-sentence examples show learners how words are typically used.More than 3,000 common idioms are defined, and an Idioms Index makes it easy to find them. Language Portraits provide in-depth explanations of difficult grammar, vocabulary, spelling, and punctuation. The dictionary also includes coverage of important Canadian and British words and meanings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.122 | 0.095 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".