(Invited) Metallic Nanocoatings on Optical Fibers as a Sensor Platform
Bibliographic record
Abstract
Deposition of gold metal on a tilted fiber Bragg grating (TFBG) demonstrates the utility of this optical fiber as a sensor for the conditions at the fiber's surface, including the continuity of a deposited metal film. Two precursors for the deposition of metallic gold are contrasted: gold(I) N'N'-dimethyl N,N”-diisopropylguanidinate (1) and gold(I) tert-butyl-imino-2,2-dimethylpyrrolidinate (2). Characterization of the deposition by optical fiber spectroscopy highlights the difference in thermal stability and growth rate of these two compounds. Compound 1 has a tremendous growth rate (220 nm/min) but is very thermally unstable, while 2 is much more thermally stable, and shows a lower growth rate of 1 nm/min.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".