9th edition of the international SOLARIS conference
Bibliographic record
Abstract
Preface The current volume represents contributed papers of the proceedings of the 9th edition of international SOLARIS conference, Chengdu, China on August 30-31, 2018. The Solaris network was created at Edinburgh Napier University after consultation amongst members from Canada, Greece, Hong Kong, Israel, Spain, UK and USA. Senior colleagues who participated in the discussions during a Specialist Conference held at Edinburgh were Emeritus Professors J L Monteith, John Page, Professors A Kudish, R Perez, T Muneer and Drs H Kambezidis, C Gueymard and staff from NREL, Colorado, USA. Immediately following the Edinburgh event a de facto Solaris governing board was established. The Solaris conference network provides a platform for meetings for professionals researching into the areas of solar radiation and daylighting to meet, solar energy conversion systems and efficient energy use in the built environment. It has a long tradition of organizing such meetings (Edinburgh 2003, Athens 2005, Delhi 2007, Hong Kong 2008, Brno 2011, Granada 2013, Maribor 2015 and London 2017). List of Keynote Speakers, Organising Committee, SOLARIS Board members, International Scientific Committee, Acknowledgements, Sponsors, Supporting Institutions, Photograph and Peer review statement are available in this pdf.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.394 | 0.274 |
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".