Characterization of optical fiber at cryogenic temperatures
Bibliographic record
Abstract
Optical fibers are commonly used for data transmission and sensing in industrial, geophysical, and aerospace markets, where they may be employed in high vacuum and cryogenic environments. The performance and integrity of optical fibers and their coatings is well understood over temperatures of ≈40 to 300 °C and pressures up to 100 atm, but their characteristics at cryogenic temperatures under high vacuum remain relatively unexplored. This study investigates the optical and mechanical reliability of selected fibers operating at cryogenic temperatures. The fiber samples under investigation were prepared with either an acrylate or polyimide coating. Several properties of the fibers were assessed, including optical loss, mechanical strength, and coating integrity. Optical loss was monitored continuously over a single temperature cycle from 300K to 4K and back. Additional samples were subjected to either one or three temperature cycles and held at 4K for extended periods. Mechanical strength of the thermally cycled fibers was determined via a 2-point bend method, and the coating material was characterized using Fourier transform infrared spectroscopy and thermogravimetric analysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".