A new current-comparator-based high-voltage low-power-factor wattmeter
Bibliographic record
Abstract
A current-comparator technique is applied to power measurements for obtaining a highly accurate high-voltage low-power-factor wattmeter. The instrument has two time-division-multiplier-type wattmeters. One wattmeter, in conjunction with a microcontroller, is used to provide automatic balancing of the quadrature component of the load current in a current comparator against a quadrature current from a current-comparator-based high-voltage quadrature reference source. The other wattmeter is used to measure the residual loss component of the load current. This new current-comparator-based high-voltage low-power-factor wattmeter has an order of magnitude improvement in accuracy and a lower measuring range in power factor than a previously developed instrument. It has an estimated uncertainty with respect to its readings of less than 0.25 percent at 0.01 power factor and higher, 0.5 percent at 0.001 power factor, and 5 percent at 0.0001 power factor.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".