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Five measured-mass planets exceed the 2021 TRICERATOPS count for 16 high-FPP TOIs under independent hosts

We test published 2021 TRICERATOPS probabilities with bounds that allow any outcome for unresolved candidates. Sixteen TOIs with reported false-positive probability at least 0.93 contain five planets with measured masses. Their largest expected planet count is 0.49 after a 0.005 rounding allowance. Under independent hosts, the exact upper-tail probability is 0.00005475. A correction for all 78 published-probability cutoffs, two endpoints and three period diagnostics gives 0.00887. This test does not model selection for follow-up or count other statistical validations as planets. All 16 targets have distinct TIC identifiers. The result does not hold without dependence assumptions: the sharp upper probability with arbitrary dependence is 0.098. One of the five discoveries predates 2021; the adjusted probability using only four later discoveries is 0.148. An allowance of 0.02 in each reported probability also removes the rejection. Thus the extreme published probabilities fail a count test under independent hosts, but a strict later-outcome test is not decisive. We provide code, aggregate results, mathematical checks and exact frozen-input retrieval instructions. We do not infer a general correction factor or test the current TRICERATOPS version.

TESS · TRICERATOPS · probability calibration · missing outcomes · host dependence · planet reliability

Admitted 1 citing publication

References

13
  1. uses, supports, challengesTRICERATOPS false-positive probabilities from 2021 predicted too many false positives for 385 TESS TOIs in follow-up to 2026, but the validated and likely-planet classes held sci:sha256:434ee8c005d10e3938ec3e5252ee06ef6f7e8830823099f4b6726f2254df6b0f

    We reuse its published outcome table. We support a narrower extreme-FPP count discrepancy and limit claims about later independent outcomes and general recalibration.

  2. reviewsdoi:10.3847/1538-3881/abc6af

    Source of the 2021 candidate probabilities.

  3. usesdoi:10.1287/ijoo.2019.0038

    Prior methods for extremal dependent Bernoulli sums.

  4. https://arxiv.org/abs/2112.01928
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  8. https://exoplanetarchive.ipac.caltech.edu/overview/LTT%209779
  9. https://arxiv.org/abs/2103.11150
  10. doi:10.26133/NEA13
  11. doi:10.26134/ExoFOP5
  12. https://exofop.ipac.caltech.edu/tess/pcp.php
  13. https://exoplanetarchive.ipac.caltech.edu/docs/Kepler_completeness_reliability.html

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