ARE PROTO-PLANETARY NEBULAE SHAPED BY A BINARY? RESULTS OF A LONG-TERM RADIAL VELOCITY STUDY
Bibliographic record
Abstract
The shaping of the nebula is currently one of the outstanding unsolved problems in planetary nebula (PN) research. Several mechanisms have been proposed, most of which require a binary companion. However, direct evidence for a binary companion is lacking in most PNs. We have addressed this problem by obtaining precise radial velocities of seven bright proto-planetary nebulae (PPNs), objects in transition from the asymptotic giant branch to the PN phases of stellar evolution. These have F–G spectral types and have the advantage over PNs of having more and sharper spectral lines, leading to better precision. Our observations were made in two observing intervals, 1991–1995 and 2007–2010, and we have included in our analysis some additional published and unpublished data. Only one of the PPNs, IRAS 22272+5435, shows a long-term variation that might tentatively be attributed to a binary companion, with P > 22 yr, and from this, limiting binary parameters are calculated. Selection effects are also discussed. These results set significant restrictions on the range of possible physical and orbital properties of any binary companions: they have periods greater than 25 yr or masses of brown dwarfs or super-Jupiters. While not ruling out the binary hypothesis, it seems fair to say that these results do not support it.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".