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
This Special Issue, guest edited by Keri Nicoll of the Universities of Reading and Bath looks at recent developments lightning detection, an important area in meteorology dating back to the early days of radio. The papers were originally presented at an RMetS National Meeting in March 2016 and cover a wide range of technology that can be used in forecasting over a range of time scales and areas. Lightning affects a large range of customers, from golfers to pilots; environmentalists to firefighters. In the first paper on p. 32, Martin Fullekrug summarises the subject, setting the scene by describing the methods used to detect lightning, which is seen not only on Earth, but also on many of the other planets of our solar system. On p. 36, Ryan Said looks at the development of global systems for the detection of lightning. At present, most operational systems cover only part of the Earth's surface (rarely more than about one‐third of the total), dependent on networks of receivers, but satellite networks and low‐frequency receivers are now making global coverage a reality, albeit with some loss of sensitivity or accuracy. Karen L. Aplin and Georg Fischer turn to lightning on other planets on p. 46. Ever since the first missions to the outer solar system in the 1970s, lightning has been seen on other planets and this paper is an excellent overview of our current knowledge, as well as plans to refine this knowledge. Our fourth paper turns to a new form of lightning detection being tested in the UK. On p. 51, Alec Bennett of Biral describes this new system that has a high degree of accuracy and sensitivity, but over relatively short ranges (100km). Finally, we turn to lightning detection from space, as described by Lorenzo Labrador on p. 54. In November and December 2016, the first two of three satellites destined for geostationary orbit were launched, carrying compatible (but different) lightning‐detection systems that will cover a range of longitude including the Atlantic, East Asia/Australasia/west Pacific and Americas. The third of these satellites will be launched in early 2019, supplementing the established ATD‐net system already providing detailed lightning location over Europe, Africa and further afield.
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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