The next generation of switchable glass : the micro-blinds
Bibliographic record
Abstract
Switchable glass or smart windows have been developed and discussed for decades. They have bright futures in applications such as vehicle, architecture, privacy and energy efficient glazing among others. The existing technologies seriously suffer from customer acceptance. The next generation of switchable glass based on micro-blinds might help the incursion of smart windows to the market, or at least to some niche markets. The micro-blinds are composed of invisible and electrostatically activated curling electrodes of 100 micrometers size. They can be deposited on flat glass by magnetron sputtering like regular low-E coatings, and then patterned by laser. They possess several advantages such as switching speed, UV durability, customized appearance and transmission, and do not employ costly ITO, relative to the current smart windows technologies: electrochromic, suspended particles and liquid crystals. Several groups have successfully developed curling electrodes for small area devices; the novelty of the proposed technology lies in the revolutionary and cost-effective processing scheme for large areas. This paper presents the status of our R&D project.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".