Science AMA Series: Hi Reddit, we’re Benoit Lavraud, Bill Peterson, and Andrew Yau. We’re all part of AGU’s Geophysical Research Letters and investigate Sun-Earth magnetic fields. Ask us anything!
Bibliographic record
Abstract
I am Benoit Lavraud, I am permanent staff researcher at the Institut de Recherche en Astrophysique et Planétologie in Toulouse - France, and Editor of Geophysical Research Letters (GRL), a research journal published by AGU focusing on high-impact scientific advances in all major geoscience disciplines. My research topics include the whole chain of phenomena occurring during solar storms between the Sun and the Earth: What are the basic processes of solar storm release? How do solar storm propagate/interact in interplanetary space? How do solar storms trigger geomagnetic activity? What are the key plasma processes controlling this interaction? Can solar and geomagnetic storms be predicted? What are the potential impacts of solar storms on society? I try to tackle these questions through both basic science and instrumentation (ion and electron spectrometers in space). I am Bill Peterson, a research associate at the University of Colorado, Boulder, at the Laboratory of Atmospheric and Space Physics. I have been studying the space weather and the coupling of the ionospheric, magnetospheric, and solar wind plasmas using satellite instrumentation since 1973. I have participated in the design, implementation, and operation of instruments on several NASA missions focused on space weather. I started out studying the physical process that that cause the aurora and the effects of the aurora on the Earth’s magnetosphere and ionosphere. I’m currently working on identifying how these processes differ at Mars using data from the MAVEN spacecraft. I am Andrew Yau, Professor of Physics at University of Calgary, Canada, and Associate Editor of Geophysical Research Letters (GRL), a research journal published by AGU focusing on high-impact scientific advances in all major geoscience disciplines. I am a space scientist. I design satellite instruments such as ion mass spectrometers, and I study the effects of weather in space on the Earth’s upper atmosphere and ionosphere. For example, how and why do solar storms and other space phenomena cause the heating of the upper atmosphere and its escape into space? How does this heating impact Earth-orbiting satellites? How does the solar wind produce the aurora, and the associated electrical currents in the ionosphere? How do these electrical currents affect radio communications - and impact the operations of satellite navigation systems such as my cell phone’s GPS receiver? We’ll be back at 11 am EST (8 am PST, 4 pm UTC) to answer your questions, ask me anything!
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.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.233 | 0.164 |
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".