Bibliographic record
Abstract
First personal computers exist since last quarter of twentieth century. Also first electronic pocket calculators exist since that time. At present they are a common and accessible element. But the need to perform mathematical calculations accurately and quickly has been a constant throughout history solved with ingenious mechanical devices. The logarithmic slide rule, is a calculation tool that facilitates rapid and comfortable performing arithmetic operations. Its use was widespread since the mid-nineteenth century until the late twentieth century, when its use declined with the appearance of the first pocket calculators and personal computers. In the seventies of the last century its use gradually disappeared. In the last decades of the twentieth century there were hardly generations of engineers who use them. Its use has been relegated to museums, organizations, friends, and to specific applications within the basic teaching of mathematics. This article gives details of basic principles of operation of the slide rules. The resources available are also displayed today to start in handling the calculation rules. Finally, they attached to article two models of paper cut-out slide rules , so that the reader can build his own rule and practice with it.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.048 | 0.050 |
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".