LIGO and the opening of a unique observational window on the universe
Bibliographic record
Abstract
A unique window on the universe opened on September 14, 2015, with direct detection of gravitational waves by the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors. This event culminated a half-century effort around the globe to develop terrestrial detectors of adequate sensitivity to achieve this goal. It also happened appropriately only a few months before the centennial of Einstein's final paper introducing the general theory of relativity. This detection provided the surprising discovery of a coalescing pair of "heavy" black holes (more massive than [Formula: see text] M[Formula: see text]) leading to the formation of a spinning [Formula: see text]62 solar mass black hole. One more binary black-hole detection and a significant candidate event demonstrated that a population of such merging binaries is formed in nature with a broad mass spectrum. This unique observational sample has already provided concrete measurements on the coalescence rates and has allowed us to test the theory of general relativity in the strong-field regime. As this nascent field of gravitational-wave astrophysics is emerging we are looking forward to the detection of binary mergers involving neutron stars and their electromagnetic counterparts, as well as continuous-wave sources, supernovae, a stochastic confusion background of compact-object mergers, known sources detected in unexpected ways, and completely unknown sources.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".