The true fraction of repeating fast radio bursts revealed through CHIME source count evolution
Bibliographic record
Abstract
ABSTRACT Fast Radio Bursts (FRBs) are classified into repeaters and non-repeaters, with only a few per cent of the observed FRB population from the Canadian Hydrogen Intensity Mapping Experiment (CHIME) confirmed as repeaters. However, this figure represents only a lower limit due to the observational biases, and the true fraction of repeaters remains unknown. Correcting for these biases uncovers a notable decline in apparently non-repeating FRB detection rate as the CHIME operational time increases. This finding suggests that a significant portion of apparently non-repeating FRBs could in fact exhibit repetition when observed over more extended periods. A simple population model infers that the true repeater fraction likely exceeds 50 per cent with 99 per cent confidence, a figure substantially larger than the observed face value, even consistent with 100 per cent. This greater prevalence of repeaters had previously gone unnoticed due to their very low repetition rates (∼10−3.5 h−1 on average). Hence, theoretical FRB models must incorporate these low-rate repeaters. Furthermore, our results indicate a significantly higher repeater volume number density, potentially exceeding observed values by up to 104 times, which in turn impacts comparisons with potential FRB progenitors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".