A 20 cm Search for Pulsars in Globular Clusters with Arecibo and the GBT
Bibliographic record
Abstract
Abstract. We are conducting deep searches for radio pulsations at L-band ( ∼ 20 cm) towards more than 30 globular clusters (GCs) using the 305 m Arecibo telescope in Puerto Rico and the 100 m Green Bank Telescope in West Virginia. With roughly three quarters of our search data analyzed, we have discovered 12 new millisecond pulsars (MSPs), 11 of which are in binary systems, and at least three of which eclipse. We have timing solutions for several of these systems. There are currently ∼76 MSPs known in 23 GCs. For the last two years we have been searching more than 30 GCs for MSPs with the Berkeley Caltech Pulsar Machine (BCPM) at the GBT and the Wideband Arecibo Pulsar Processor (WAPP) at Arecibo. The high time and frequency resolution of these data, along with newly developed search algorithms (Ransom, Eikenberry, & Middleditch 2002; Ransom, Cordes, & Eikenberry 2003), makes us significantly more sensitive than past surveys to sub-millisecond pulsations as well as pulsars in ultra-compact binary systems. So far we have discovered 12 new MSPs in 6
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".