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
The SETIS magazine aims at delivering timely information and analysis on the state of play of energy technologies, related research and innovation efforts in support of the implementation of the European Strategic Energy Technology Plan (SET-Plan). The current issue is dedicated to Energy Systems Modelling\n\nThe editorial for the Energy Systems Modelling issue is provided by Dr Jan Nill at the European Commission’s Directorate-General for Climate Action. This issue also hosts interviews with:\n•\tDavid Connolly – coordinator of the H2020 project "Head Roadmap Europe" and one of the developers of the EnergyPLAN model;\n•\tMarc Oliver Bettzüge – director of the Institute of Energy Economics at the University of Cologne (ewi); Alistair Buckley - co-author of ‘A review of energy systems models in the UK: Prevalent usage and categorisation’; and\n•\tMark O'Malley – director of the International Institute for Energy Systems Integration.\n\nThree contributors from the European Commission’s Directorates-General for Climate Action, Energy and Mobility and Transport collaborate on an article on the EU Reference Scenario 2016, one of the European Commission’s key analysis tools used in the context of the Energy Union. We also have a contribution from DG Energy on the METIS energy system model - a research project for the development of energy simulator software with the aim to further support DG ENER’s evidence-based policy-making. Finally, the Joint Research Centre Directorate C - Energy, Transport and Climate contributed to an article on the importance of open data and software for energy research and policy advice.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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