Bibliographic record
Abstract
Abstract As with all binaries, those that contain massive stars reveal various degrees of interaction, depending mainly on orbital separation and age, although things happen much faster in massive binaries. Those massive binaries with initial periods exceeding ~10 years generally only interact via wind-wind collisions, with little or no effect on their subsequent evolution (unless located in dense clusters). Shorter-period systems show even stronger wind-wind collisions as a rule, but also interact more directly via Roche Lobe Overflow or Common Envelope, with dramatic effects on their evolution. If we didn't have binaries among massive stars, we would be missing a whole host of interesting phenomena in the Universe, such as sources of enhanced stellar X-ray or non-thermal radio emission, WR dust-spirals, inverse mass-ratios, very rapid spin, rejuvenation and massive blue-stragglers, enhanced cluster dynamics, many runaways and possibly even SMBHs and GRBs! On the other hand, non(or little)-interacting massive binaries are also useful to provide information on Star-Formation processes and determination of stellar parameters (such as the mass) that would otherwise be difficult or impossible to obtain from single stars. In this review, I highlight some of the developments that have occurred during the past few years since the last IAU Symposium on Massive Stars in 2002.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".