Additional Keplerian Signals in the HARPS data for Gliese 667C: Further Analysis
Bibliographic record
Abstract
Abstract A re-analysis of Gliese 667C HARPS precision radial velocity data was carried out with a Bayesian multi-planet Kepler periodogram (from 0 to 7 planets) based on a fusion Markov chain Monte Carlo algorithm. The most probable number of signals detected is six with a Bayesian false alarm probability of 0.012. The residuals were shown to be consistent with white noise. The six signals detected include two previously reported with periods of 7.198 (b) and 28.14 (c) days, plus additional periods of 30.82, 38.82, 53.22, and 91.3 days. The existence of these Keplerian-like signals suggest the possibility of additional planets in the habitable zone of Gl 667C although some of the signals could be artifacts arising from the sampling or stellar surface activity. N-body orbital integrations are being undertaken to determine which of these signals are consistent with a stable planetary system. Preliminary results demonstrate that four of the signals, with periods of 7.2, 28.1, 38.8, & 91 d, are consistent with a stable 4 planet system on time scales of 107 yr. The M sin i values are ~5.5, 4.4, 1.9, and 4.7 M⊕, respectively.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".