The Emilia-Romagna System for Start-Up Growth
Bibliographic record
Abstract
EmiliaRomagnaStartup (ERSU) is one of the pillars of the Emilia-Romagna regional policy to promote innovative business creation. Launched in 2011, it represents nowadays one the most developed regional instruments at EU level to support start-up creation through information, orienteering, services provision and networking opportunities. The initiative is coordinated by ASTER, the regional Consortium for Innovation and Technology Transfer. Designed by ASTER Start-up Dept on the basis of an intensive benchmark activity to provide up-to-date services, today it is constantly improving the variety and the quality of its offer which is directed to start-ups and business projects, but also to the various regional actors that are part of its network. Initiatives such as sector-focused acceleration programs (e.g. on Green or Creative sectors), opportunities to go global (through, for instance, the partnership with the Tech Venture Launch Program in Silicon Valley) and planning of new services through the participation in EU projects, represent the key added value ERSU can offer to its community of users.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.028 |
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".