Optical models for the ellipsometric characterisation of porous silicon structures
Bibliographic record
Abstract
Thick porous silicon layers were prepared by electrochemical etching on n- and p-type single-crystalline silicon substrate, and characterised by spectroscopic ellipsometry and complementary techniques. The layers were thicker than the penetration depth of light for all wavelengths, so the samples were assumed to be bulk porous material. Best fit was obtained using two-layer models taking into account the surface inhomogeneity. The microstructure of the porous material was characterised using effective medium models with dielectric function reference spectra from the literature or calculated by model dielectric functions (MDF). Using the MDF model, reference dielectric function spectra were generated with different broadening parameters. A good agreement was found between the porosity obtained by ellipsometry and Brillouin scattering. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".