TRACK – A new method for the evaluation of low-level extinction coefficient in optical films
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Bibliographic record
Abstract
We develop a rigorous methodology named TRACK based on the collection of multi-angle spectrophotometric transmission and reflection data in order to assess the extinction coefficient of quasi-transparent optical films. The accuracy of extinction coefficient values obtained by this method is not affected by sample non-idealities (thickness non-uniformity, refractive index inhomogeneities, anisotropy, interfaces, etc.) and therefore a simple two-layer (substrate/film) optical model can be used. The method requires the acquisition of transmission and reflection data at two angles of incidence: 10° and 65° in p polarization. Data acquired at 10° provide information about the film thickness and the refractive index, while data collected at 65° are used for absorption evaluation and extinction coefficient computation. We test this method on three types of samples: (i) a CR-39 plastic substrate coated with a thick protective coating; (ii) the same substrate coated with a thin TiO(2) film; (iii) and a thick Si(3)N(4) film deposited on Gorilla glass that presents thickness non-uniformity and refractive index gradient non-idealities. We also compare absorption and extinction coefficient values obtained at 410 and 550 nm by both TRACK and Laser Induced Deflection techniques in the case of a 1 micron thick TiO(2) coating. Both methods display consistent extinction coefficient values in the 10(-4) and 10(-5) ranges at 410 and 550 nm, respectively, which proves the validity of the methodology and provides an estimate of its accuracy limit.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it