ESSenTIAL: EPIXfab services specifically targeting (SME) industrial takeup of advanced silicon photonics
Bibliographic record
Abstract
ePIXfab brings silicon photonics within reach of European small and medium sized enterprises, thereby building on its track record and its integration into Europractice. To this end, ePIXfab offers affordable access to standardized active and passive silicon photonic IC and packaging technology, a path from design to manufacturing and hands-on training. Based on a consortium of major research institutes with silicon photonics expertise, ePIXfab reaches out to European industry and supports them to evaluate silicon photonics in the context of concrete applications and markets. In order to ensure low-cost, quick access and scalability to manufacturing, the maturity of silicon photonic IC technology is enhanced by setting up a library of generic devices, a level of process and device benchmarking and a well maintained design flow. For the first time, devices in a standard package are offered to facilitate measurements. Training programs on the IC and packaging services are also offered, including hands-on training in making designs. Maturity, standardization and sustainability are driven by a steadily growing worldwide user base.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.445 | 0.235 |
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".