CENTAURS: Highlights from the new book and the Next Ten Years for Centaur Research
Bibliographic record
Abstract
Centaurs are an unstable, transitional population of small, icy bodies connecting the Jupiter-family comets (JFCs) to their reservoir population in the trans-Neptunian region. Due to the more extreme thermal environment of the giant-planet region relative to that of the trans-Neptunian objects (TNOs), Centaurs experience rapid dynamical and physical changes, thermophysically evolving these otherwise well-preserved objects. Many of these physical changes may be seen in the surface topography, ices, and refractory composition and volatiles emitted from active Centaurs. The dawn of several new observational assets and laboratory techniques whose data will be augmented with dramatically increased computing power indicates that Centaur research is at the start of a transformational era. Here we briefly summarize some of the foundational discoveries covered in earlier chapters of the new book CENTAURS and review what is needed to make significant progress on outstanding problems. We also present and discuss eight Centaur Priority Goals for the next ten years that we put in context of the 2023 U.S. National Academies of Sciences, Engineering, and Medicine’s decadal survey for Planetary Science and Astrobiology.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.044 | 0.036 |
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".