The Green Bank North Celestial Cap Survey. VII. 12 New Pulsar Timing Solutions
Bibliographic record
Abstract
Abstract We present timing solutions for 12 pulsars discovered in the Green Bank North Celestial Cap 350 MHz pulsar survey, including six millisecond pulsars (MSPs), a double neutron star (DNS) system, and a pulsar orbiting a massive white dwarf companion. Timing solutions presented here include 350 and 820 MHz Green Bank Telescope data from initial confirmation and follow-up, as well as a dedicated timing campaign spanning 1 ryr PSR J1122−3546 is an isolated MSP, PSRs J1221−0633 and J1317−0157 are MSPs in black widow systems and regularly exhibit eclipses, and PSRs J2022+2534 and J2039−3616 are MSPs that can be timed with high precision and have been included in pulsar timing array experiments seeking to detect low-frequency gravitational waves. PSRs J1221−0633 and J2039−3616 have Fermi Large Area Telescope gamma-ray counterparts and also exhibit significant gamma-ray pulsations. We measure proper motions for three of the MSPs in this sample and estimate their space velocities, which are typical compared to those of other MSPs. We have detected the advance of periastron for PSR J1018−1523 and therefore measure the total mass of the DNS system, m tot = 2.3 ± 0.3 M ⊙. Long-term pulsar timing with data spanning more than 1 yr is critical for classifying recycled pulsars, carrying out detailed astrometry studies, and shedding light on the wealth of information in these systems post-discovery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".