Western Canadian Contributions to Librariansbip GUIDE TO LITERATURE OF ELECTRONICS
Bibliographic record
Abstract
s not only list articles under subject headings, but also give summaries of their con tents. They are therefore much more useful than indexes, since you can often tell from the abstract that the article will, or will not, be useful. You should read the introduction and instructions for use with care, for abstracts vary a good deal in arrangement and methods. Look out for cumulative indexes to both ab stracts and indexes, which can save your having to look through several volumes; and keep in mind that you may find information under more than one heading. For instance, when looking for information about semi-conductors, you should also use headings such as transis tors and germanium. Applied science and technology index, 1913 Monthly. (Old title: Industrial arts index.) Up-to-date cumulations, general coverage.) Chemical abstracts. 1907Semi monthly. (For solid-state physics, semi conductors, etc. Classified arrangement. Subject indexes year ly.) Gt. Brit. Department of Scientific and Indus trial Research. Radio Research Organization. Abstracts and references. (These abstracts were issued by D.S.I.R. until the end of 1962, and published in Electronic technology and in the Proceedings of the Institute of Radio Engineers. Engineering index. 1884Annual. (Abstracts, international in scope. Not as useful as Science abstracts.)
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.044 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.459 | 0.370 |
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".