[no title]
Bibliographic record
Abstract
The joint detection of gravitational waves (GWs) and electromagnetic radiation from the binary neutron star (BNS) merger GW170817 has provided unprecedented insight into a wide range of physical processes: heavy element synthesis via the r-process; the production of relativistic ejecta; the equation of state of neutron stars and the nature of the merger remnant; the binary coalescence timescale; and a measurement of the Hubble constant via the "standard siren" technique. In detail, all of these results depend on the distance to the host galaxy of the merger event, NGC 4993. In this Letter we measure the surface brightness fluctuation (SBF) distance to NGC 4993 in the F110W and F160W passbands of the Wide Field Camera 3 Infrared Channel (WFC3/IR) on the Hubble Space Telescope (HST). For the preferred F110W passband we derive a distance modulus of $(m-M)\\,=33.05\\pm 0.08\\pm 0.10$ mag, or a linear distance d = 40.7 ± 1.4 ± 1.9 Mpc (random and systematic errors, respectively); a virtually identical result is obtained from the F160W data. This is the most precise distance to NGC 4993 available to date. Combining our distance measurement with the corrected recession velocity of NGC 4993 implies a Hubble constant H 0 = 71.9 ± 7.1 km s−1 Mpc−1. A comparison of our result to the GW-inferred value of H 0 indicates a binary orbital inclination of i gsim 137°. The SBF technique can be applied to early-type host galaxies of BNS mergers to ~100 Mpc with HST and possibly as far as ~300 Mpc with the James Webb Space Telescope, thereby helping to break the inherent distance-inclination degeneracy of the GW data at distances where many future BNS mergers are likely to be detected.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".