Bibliographic record
Abstract
It is our pleasure and honour to introduce this prestigious publication – The Proceedings of the Institute of Physics International Conferences Electrostatics 2019 and Dielectrics 2019. The conferences were organised by the Dielectrics & Electrostatics Group of the Institute of Physics, and for the first time were co-located in the historic city of Manchester, UK from 8th to 12th April 2019. Electrostatics 2019 was the 15th conference in the series since its inauguration 66 years ago. The conference has been held at many venues around the UK, but this was the first time in Manchester. We are proud to say that is was something of a home coming for electrostatics as two of the founders of the Electrostatics Group, then known as the Static Electrification Group, were based in Manchester: Dr N Gibson and Dr P S H Henry. This year also marks the 46th Anniversary of the Dielectrics Group, which is now part of the Dielectrics & Electrostatics Group, and was formerly the Dielectrics Society. Manchester is the second largest city in Great Britain. The city is also home to many discoveries. The luxury car company Rolls-Royce was first established in Manchester in 1904. In the late 1940’s, professors at Manchester University developed the first computer that had a stored programme and memory. More recently, graphene, also known as a wonder material, was first extracted by two professors at Manchester University: Sir Andre Geim and Sir Kostya Novoselov, for which they were awarded the Noble prize in Physics in 2010. The world’s first intercity railway was designed and built by the great George Stephenson was opened in 1830, operating between Manchester and Liverpool. Manchester is also famous for its cotton industry and was even known as Cottonopolis in the 19th century. Electrostatics 2019 spanned across four days and included fifteen oral presentation sessions and three poster presentation sessions. The final two sessions of Electrostatics 2019 were joint sessions forming the first two sessions of Dielectrics 2019, which continued into the fifth day with a total of seven oral presentation sessions and one poster presentation session. The conferences were truly international with delegates attending from across the globe: Australia, Austria, Belgium, Canada, Czech Republic, Finland, France, Germany, Hong Kong, Hungary, India, Ireland, Japan, South Korea, Lebanon, Mexico, Poland, Portugal, Qatar, Spain, Sweden, Switzerland, Tunisia, USA and, of course, United Kingdom. There was also a balanced representation between academic/research institutions (∼60%) and industry (∼40%), which was an added highlight of the conference. There were a significant number of research students attending and presenting their work, which was really an exciting benefit as students will be our future scientists/professors/CEO’s. There were also exhibitors, who were very active and lively in engaging with the delegates.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.551 | 0.422 |
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".