Topical Meeting on Optical Interference Coatings (OIC’2001): manufacturing problem
Bibliographic record
Abstract
Measurements are presented of the experimental filters submitted to the first optical thin-film manufacturing problem posed in conjunction with the Topical Meeting on Optical Interference Coatings, in which the object was to produce multilayers with spectral transmittance and reflectance curves that were as close as possible to the target values that were specified in the 400- to 600-nm spectral region. No limit was set on the overall thickness of the solutions or the number of layers used in their construction. The participants were free to use the coating materials of their choice. Six different groups submitted a total of 11 different filters for evaluation. Three different physical vapor deposition processes were used for the manufacture of the coatings: magnetron sputtering, ion-beam sputtering, and plasma-ion-assisted, electron-beam gun evaporation. The solutions ranged in metric thickness from 758 to 4226 nm and consisted of between 8 and 27 layers. For all but two of the samples submitted, the average rms departure of the measured transmittances and reflectances from the target values in the spectral region of interest was between 0.98% and 1.55%.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".