Terahertz refractometry of hard-to-access objects using the sapphire endoscope suitable for harsh environments
Bibliographic record
Abstract
While terahertz (THz) technology offers a variety of applications in medical diagnosis, nondestructive testing, and quality control, its acceptance in these practical fields is hampered by the absence of endoscopic systems, capable of sensing the complex refractive index of the hard-to-access objects. In this paper, we develop the THz endoscope based on the hollow-core antiresonant waveguide, formed by a polytetrafluoroethylene (PTFE)-coated sapphire tube with the outer end closed by a monolithic sapphire window. The endoscope is attached to the backward wave oscillator spectrometer to measure the sample reflectivity. By studying the well-known liquid and solid samples, we demonstrate that analysis of the Fabry–Pérot resonance in the measured reflection spectra makes it possible to quantify the complex refractive index of an analyte. Thanks to the advanced chemical inertness and thermal strength of sapphire and PTFE, the developed endoscope is capable of operation in harsh environments, which broadens the range of its applications. Our findings pave the way for the THz technology use in a number of demanding practical fields.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".