A Lack of Planets in 47 Tucanae from a [ITAL]Hubble Space Telescope[/ITAL] Search
Bibliographic record
Abstract
We report results from a large Hubble Space Telescope project to observe a significant (~34,000) ensemble of main-sequence stars in the globular cluster 47 Tucanae with a goal of defining the frequency of inner orbit, gas giant planets. Simulations based on the characteristics of the 8.3 days of time series data in the F555W and F814W Wide Field Planetary Camera 2 (WFPC2) filters show that ~17 planets should be detected by photometric transit signals if the frequency of hot Jupiters found in the solar neighborhood is assumed to hold for 47 Tuc. The experiment provided high-quality data sufficient to detect planets. A full analysis of these WFPC2 data reveals ~75 variables, but no light curves resulted for which a convincing interpretation as a planet could be made. The planet frequency in 47 Tuc is at least an order of magnitude below that for the solar neighborhood. The cause of the absence of close-in planets in 47 Tuc is not yet known; presumably the low metallicity and/or crowding of 47 Tuc interfered with planet formation, with orbital evolution to close-in positions, or with planet survival.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".