A dimensionless joint density of states formalism for the quantitative characterization of the optical response of hydrogenated amorphous silicon
Bibliographic record
Abstract
We simplify the empirical model of O’Leary and Malik [J. Appl. Phys. 92, 4276 (2002)] for the density of state functions associated with hydrogenated amorphous silicon, reducing the number of independent modeling parameters from six to five as a result. As a consequence of this simplification, we find that we are able to cast our joint density of states (JDOS) evaluations into a dimensionless formalism, this formalism providing an elementary and effective platform for the determination of the underlying modeling parameters from experiment. We then justify our simplification by showing, for reasonable hydrogenated amorphous silicon modeling parameter selections, that our JDOS results are very similar to those determined using the more general approach of O’Leary and Malik. We also show that this simplified model is as effective as its predecessor in capturing the results of experiment. Finally, we demonstrate the utility of our dimensionless JDOS formalism, using it for the purposes of performing a critical comparative analysis of three different hydrogenated amorphous silicon optical absorption data sets.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".