Bibliographic record
Abstract
Northern Ireland’s natural resource environment is ‘brimming with home grown’ energy opportunities including; a diverse and thermally-rich geology, windy undulating drumlins, and maritime zones; moreover, an emerging array of renewable technology projects, some of which are under consideration, in-progress or completed. We are arguably in a time period when some of the greatest energy changes are a foot – ‘a golden age’, so to speak. Staying on top of, and up-to-date with, this ever-changing energy environment is no small task. Data repositories, reports, websites, and social media feeds all help. Organising workshops too can serve to inform, energise, and mobilise networks, further collective network goals, build confidence, kick-start collaborations, and hatch as well as spur project ideas and capital investments. This workshop briefing note reports on all of the above. Held on the 4th July 2023 and entitled ‘Building the Geothermal Energy Sector in Northern Ireland,’ the workshop was co-organised and co-hosted by Queen’s University Belfast with the Northern Ireland Housing Executive. It comprised multi-stakeholders, as well as keynote speakers, panel discussions, and question and answer sessions. Significantly, our workshop also marked the construction completion of the new Business School building at Riddel Hall, which, coincidently has a geothermal heating system. With 120 participants in attendance, our workshop aimed to provide practitioner-led project updates across the geoenergy nexuses. Richard Rodgers, Head of Energy and Deputy Secretary of the Department for the Economy opened our workshop, before keynote presentations by Dr Matt Trewhella, Chief Executive Officer, Kensa Group, and Sara Lynch, Head of Sustainability, Estates Directorate, Queen’s University Belfast. The workshop activities overall generated a range of thoughtful conversations and discernible themes: Theme 1 — More awareness of established geoenergy blueprint elsewhere in the United Kingdom and further afield. Kensa Heat Pumps Ltd demonstrated exemplary cases of geothermal and ground source heat pump (GSHP) applications from across the UK. Theme 2 — Increase emphasis and overlap in both the quality and energy trilemma issues in the energy transition. Theme 3 — Government subvention support, political engagement and big society conversations beyond the important strides made with the NI Energy Strategy Action Plan 2022, Heat Policy frameworks. Theme 4 — Significant value co-creation and socialisation of costs by pivoting and collaboratively working across ecosystem nexuses. Integrated data fusion thinking between geology, front-end heating engineering and business models. Theme 5 — Behavioural change among consumers will be an important component of the level of decarbonisation envisaged with retrofitting of homes, heat pump switching, heat demand optimisation, and heat network development. Theme 6 — Leapfrog pathway development with general UK policy and the Energy Bill to close and progress the legislation gaps between the NI Utility Regulator and Ofgem. Also, increase the local Assembly or policy-makers’ capacity to bring forward legislation commensurate with the other devolved UK governments. Overall therefore, our main conclusion from the workshop is that sector-building efforts require the pivoting of the geoenergy nexuses towards multiple ecosystems. Developing the different geoenergy ecosystem perspectives and pivoting with the 10-point axis are additional key focus areas for sector-building and policy development.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.021 | 0.025 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.056 | 0.009 |
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".