New developments in the determination of the complex refractive index of arbitrary absorptance thin films from envelope profiles of a single transmittance curve
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Bibliographic record
Abstract
Recently, a simple and self-consistent formalism that accurately gives the complex refractive index η = n - iκ of arbitrary absorptance thin films from a single transmittance curve has been introduced. Without any approximation, this analysis method makes use of a “corrected transmittance curve” for which the transmittance maxima values reach 1. With actual values of n(λ) and κ(λ), this last condition must be fulfilled. When these dispersion curves are not known, the method remains valid, but one must rely on “initial approximate dispersion curves” obtained by any mean, including theoretical formulations. In addition, this method shows that when the envelope profiles of transmittance curves are known, the need to determine initial approximate dispersion curves is not required. The challenge lies in finding the actual envelope profiles. Here, we show new developments on procedures to extract the envelope profiles. In case of weak absorption, using cubic spline interpolations, this can be done with little to no error, except for experimental and computational ones. In case of strong absorption bands, the slope in the transmittance curve shifts the extrema, which no longer correspond to the tangent points with their respective envelopes. This is remedied by applying a “rectifying process” that gives a “partially corrected transmittance curve”, which then leads to a fully corrected curve. However, in case of strong and narrow absorption bands, the small number of transmittance fringes might reduce the accuracy. Then, the reflectance curve appears beneficial to circumvent this weakness.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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