Bibliographic record
Abstract
Abstract The surface resistance R s of superconducting materials can be obtained by measuring the quality factor of an elliptical cavity excited in a transverse magnetic mode (TM 010 ). The value obtained has however to be taken as averaged over the whole surface. A more convenient way to obtain R s , especially of materials which are not yet technologically ready for cavity production, is to measure small samples instead. These can be easily manufactured at low cost, duplicated and placed in film deposition and surface analytical tools. A commonly used design for a device to measure R s consists of a cylindrical cavity excited in a transverse electric (TE 110 ) mode with the sample under test serving as one replaceable endplate. Such a cavity has two drawbacks. For reasonably small samples the resonant frequency will be larger than frequencies of interest concerning SRF application and it requires a reference sample of known R s . In this article we review several devices which have been designed to overcome these limitations, reaching sub-nΩ resolution in some cases. Some of these devices also comprise a parameter space in frequency and temperature which is inaccessible to standard cavity tests, making them ideal tools to test theoretical surface resistance models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".