Science AMA Series: In 1915, Einstein published his general theory of relativity. How are scientists using Einstein’s theory today? We cover physics and astronomy for Science News. Ask us anything!
Bibliographic record
Abstract
Hi reddit! We are the astronomy and physics writers for Science News (https://www.sciencenews.org/), a publication of the Society for Science and the Public (https://www.societyforscience.org/). This November marks the 100-year anniversary of Einstein’s General Theory of Relativity. To celebrate, we published a special issue of Science News focusing on how researchers are using Einstein’s theory today–from using it to magnify the cosmos to exploring quantum entanglement. About Andrew Grant: I am an award-winning physics writer for Science News. I have a bachelor’s degree in physics from The College of New Jersey and a master’s in journalism from New York University’s Science, Health and Environmental Reporting Program. My story (“Entanglement: Gravity’s long-distance connection”: https://www.sciencenews.org/article/entanglement-gravitys-long-distance-connection) examines a big idea to expand the scope of general relativity that involves black holes, wormholes, holograms and a mysterious phenomenon called quantum entanglement. Physicists are exploring whether long-distance quantum connections are responsible for the geometry of space and time in the universe. About Christopher Crockett: I am the astronomy writer for Science News. I received by Ph.D. in astronomy from the University of California, Los Angeles. After eight years of searching for exoplanets, probing distant galaxies and exploring comets, I realized I enjoyed talking about astronomy a lot more than actually doing it. After being awarded a 2013 AAAS Mass Media Fellowship to write for Scientific American, I left a research career at the U.S. Naval Observatory to pursue a new life writing about anything and everything within the local cosmological horizon. I joined Science News in early 2014. My story (“Using general relativity to magnify the cosmos”: https://www.sciencenews.org/article/using-general-relativity-magnify-cosmos?mode=pick&context=163) explores how scientists exploit phenomena predicted by the general theory of relativity to study the universe. We here to answer your questions about Einstein’s General Theory of Relativity and how scientists are using it today! We’ll be back at 2pm ET (11am PT) to answer your questions! Ask us anything! EDIT: Thanks for the awesome questions! We had a blast. We’ll be checking in throughout the day to answer more questions. Until next time!
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.192 | 0.126 |
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".