Bibliographic record
Abstract
Measuring small inductors and capacitors can be challenging with the use of conventional LCR-meters that have a test frequency of 10 kHz or less. With a 10 nH inductor at 10 kHz, the impedance is only 6 mOhms, that is comparable to the resistance of the probes. At a frequency of 100 kHz, the impedance increases to 60 mOhms. On the other hand, a 1 pF capacitor at 10 kHz results in an impedance of 15 MOhms, which makes a capacitive connection between the probes noticeable and affects the measurement of impedance. This paper presents two case studies: an extraction the parasitic inductance of the two-wire probes using the HP4284A LCR-meter and HP16034E test fixture, and extraction of the parasitic capacitance using the LCR-Reader-R2 tweezer-meter. This method enables accurate measurements of sub-nH inductors and sub-pF capacitors using test frequencies below 300 kHz.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".