H2020 Platone Italian Demonstrator Use Case 1-2 Market 1st quarter 2022
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
areti_market_flexibility_TSO_requestes areti_market_flexibility_DSO_requestes areti_market_flexibility_Aggregator_bids areti_market_flexibility_settlement areti_market_flexibility_outcomes - TSO flexibility requests: Starting Time Duration Market Type Market Session Flexibility Service Type Volumes Grid Area - DSO flexibility requests: Starting Time Duration Market Type Market Session Flexibility Service Type Volumes, Grid Area - Aggregator bids: Starting Time Duration Market Type Market Session Flexibility Service Type Volumes PoDs List - Settlement data: Pod Requested Active Power Measured Active Power Requested Reactive Power Measured Reactive Power - Market Outcomes: Market Outcome Id Market Type Market Session Flexibility Service Type Other than TSO flexibility requests, to test the demo, other data could be simulated. In this case, it will be indicated in the metadata documentation. (Useful link to consult Italian UC: https://smart-grid-use-cases.github.io/docs/usecases/platone/uc-it-1-voltage-management/; https://smart-grid-use-cases.github.io/docs/usecases/platone/uc-it-2-congestion-management/, https://platone-h2020.eu/data/deliverables/864300_M12_D1.1.pdf)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.050 |
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 it