Pith. sign in

REVIEW 3 major objections 4 minor 39 references

Secular Perturbations from Exterior Giants Strongly Influence Gap Complexity in Peas-in-a-Pod Exoplanetary Systems

T0 review · 3 major / 4 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read Outer giant planets can create irregular spacings in inner exoplanet systems after formation.

desk verdict A credible secular mechanism for the OG gap-complexity dichotomy, but the quantitative case depends on a favorable line-of-sight choice that needs a proper observational selection model before the claim fully lands. read the letter →

arxiv 2412.18661 v1 pith:G6KWRCJO submitted 2024-12-24 astro-ph.EP

classification astro-ph.EP
keywords exoplanetdynamicsgapcomplexitysecularperturbationsLaplace-LagrangetheorypeasinapodoutergiantplanetstransitgeometryKepler/KGPSsample
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Kepler surveys show that systems of tightly packed inner planets (STIPs), the 'peas in a pod' systems, tend to have less regular orbital spacings when a giant planet orbits farther out, and more regular spacings when the outer companion is a star. This paper tests whether that observed dichotomy can be produced after the planets form, purely by the long-term secular gravitational tug of the outer giant on the inner system. Using Laplace-Lagrange secular theory, the authors evolve 2,500 initial condition sets in each of five ensembles (12,500 simulations) both with and without an outer giant, and compute the time-averaged gap complexity $\langle \tilde{C}\rangle$ along a favorable observing direction. They find that outer giants raise the average gap complexity by between +0.036 and +0.062 depending on STIP multiplicity, with the biggest increases coming from massive, close-in giants. If correct, secular dynamics alone can explain the statistical gap-complexity dichotomy, with no need to invoke formation-stage effects.

What carries the argument

The load-bearing machinery is second-order Laplace-Lagrange secular theory for the inclination degrees of freedom, in which an $N\times N$ matrix $\mathbf{B}$ built from Laplace coefficients determines the eigenfrequencies and eigenmodes of each planet's inclination vector. The strength of the outer companion's forcing enters through the secular effective mass, $m_k \alpha_{jk}\bar{\alpha}_{jk} b^{(1)}_{3/2}(\alpha_{jk})$, which is about two orders of magnitude larger for a typical giant planet than for a stellar companion; this ratio is what lets the model reproduce both halves of the observed dichotomy. The observable is the gap complexity $C$ of Gilbert & Fabrycky, a convex complexity that combines the Shannon entropy and disequilibrium of the normalized log-period spacings $p^\star_i$. For each of 12,500 simulations, the paper compares the time-averaged value $\langle \tilde{C}\rangle$ with and without the outer giant, using the line of sight perpendicular to the line of nodes and lying in the mean inclination plane of the inner system. The secular approximation is checked against N-body integrations with a Wisdom-Holman integrator and found to match up to the Hill stability boundary.

What would settle it

Take the same 2,500-condition ensembles and compute the gap-complexity difference using lines of sight drawn from an isotropic distribution of observer orientations instead of always the favorable perpendicular geometry; if the ensemble-average difference between STIPs with and without outer giants is no longer positive, the proposed explanation of the observed dichotomy fails. A second, observational check is to compare the predicted fraction of STIP+OG systems that would appear as one- or two-transiting-planet systems with the multiplicity rates in the Kepler/KGPS sample; a large mismatch would rule out secular forcing as the dominant cause.

Watch

Extended reading notes

Core claim

The paper's central claim is that secular perturbations from an exterior giant companion can account for the gap-complexity dichotomy that He & Weiss (2023) measured in the Kepler/KGPS sample. The giant adds a new mode to the Laplace-Lagrange inclination solution of the inner system; that mode amplifies the planets' mutual inclinations, so each planet spends more time tilted out of the transiting plane. Since gap complexity is computed only from the planets currently seen in transit, a missing planet changes the normalized log-spacing weights $p^\star_i$ in the definition of $C$ and produces artificial gaps. Averaged over long integrations and over each 2,500-realization ensemble, the presence of an outer giant increases the time-averaged gap complexity by +0.036 ($N=4$, $I_{\rm OG}=10^\circ$) to +0.062 ($N=6$, $I_{\rm OG}=10^\circ$), while in some individual parameter regions the sign is reversed. The same framework explains why stellar companions do not show the effect: their secular effective mass is roughly two orders of magnitude smaller, so the induced inclination forcing is too weak.

Load-bearing premise

The quantitative results assume the observer's line of sight is always the most favorable one, perpendicular to the line of nodes and in the mean inclination plane of the inner system, rather than a random or typical observing geometry.

Editorial extensions

If this is right

  • If correct, the observed STIP+OG gap-complexity dichotomy can be explained without invoking a formation-stage mechanism; post-formation secular forcing alone raises the time-averaged gap complexity by the amount seen in the Kepler/KGPS sample.
  • The model predicts that gap-complexity enhancement should be strongest for massive, close-in outer giants and absent or weak for distant stellar companions, matching the sample positions of OG and SC systems in the secular-effective-mass plane.
  • Because individual simulations show both positive and negative changes, the population-level trend is not a deterministic statement about any one system; individual STIP+OG systems can have lower gap complexity than their no-giant counterparts.
  • Systems whose inner planets are frequently knocked out of transit will sometimes be observed as one- or two-planet systems, so gap-complexity samples are biased toward the sub-population that remains multi-transiting, an effect the paper identifies as a limitation of the metric.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The favorable-line-of-sight assumption implies a testable census prediction: if secular forcing is the cause, STIP+OG populations should show an elevated fraction of systems observed with fewer transiting planets than their true multiplicity, compared with STIP-only populations.
  • Repeating the calculation with isotropically distributed observer lines of sight could shrink or reverse the average +0.036 to +0.062 shift, so the strength of the explanation depends on how strongly Kepler-style detection selects systems with many transiting planets.
  • Because only second-order secular theory is used, eccentricity-inclination coupling effects such as Lidov-Kozai oscillations are omitted; including them could alter the gap-complexity evolution on long timescales, particularly for highly inclined outer giants.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper proposes a dynamical explanation for the observed trend that systems of tightly packed inner planets (STIPs) with exterior giant companions (OGs) have higher observed gap complexity than those without. The authors use second-order Laplace–Lagrange secular theory to evolve the inclinations of idealized STIPs with and without an OG, then compute the time-averaged gap complexity along a line of sight chosen to maximize the chance of seeing at least three transiting planets. Across 12,500 simulation pairs, they find ensemble-mean increases in gap complexity of +0.036 to +0.062 when an OG is present (Figure 5), and argue that this secular mechanism can account for the He & Weiss (2023) dichotomy between OG and stellar-companion (SC) systems.

Significance. If the central claim holds, the paper would provide a plausible post-formation dynamical mechanism for a statistically significant observational dichotomy, connecting secular inclination forcing to a population-level observable. The study is not circular: no parameters are fitted to the He & Weiss dichotomy; the model inputs (period-ratio spacing, Rayleigh inclination distribution, companion mass and semi-major axis ranges) come from independent literature, and the result emerges generically from forward secular evolution. The paper also ships reproducible code (GitHub and Zenodo) and includes limited N-body validation in Section 2.4. However, the quantitative conclusion rests on a specially chosen viewing geometry and on an unspecified stellar radius, which currently limits the strength of the comparison to the observed Kepler/KGPS sample.

major comments (3)
  1. [Section 2.3, footnote 4 and Figure 5] This is load-bearing because the abstract and conclusions directly compare the simulated time-averaged gap complexity to the observed C distributions.
  2. [Equation (18) and Section 2.3] A referee cannot reproduce the results without this parameter.
  3. [Section 4.1] This issue is load-bearing because the paper's stated goal is to explain a statistical dichotomy, not merely to show that an increase is possible in some geometries.
minor comments (4)
  1. [Section 2.4] The GitHub repository is mentioned, but the paper should be self-contained for this key check.
  2. [Section 3, Figure 5 caption] This is a clarity issue, not a correctness issue.
  3. [Section 2.3, Equation (13)] This is a minor caveat for the idealized setup.
  4. [Table 1] The table caption notes the mass approximation, but the small number of systems is not discussed.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the model's gap-complexity predictions are forward-modeled from independent literature inputs, not fitted to the target dichotomy.

full rationale

The paper's central comparison is not circular. The input distributions (spacing law from Weiss et al. 2018, inclinations from Fabrycky et al. 2014, masses and semimajor axes from a uniform grid) are independent of the He & Weiss (2023) gap-complexity dichotomy that the paper aims to explain. Gap complexity is computed from the simulated transit geometry via Eqs. (1)-(2), and the OG/SC difference emerges from the Laplace-Lagrange secular matrix (Eqs. 3-4) rather than being imposed. No parameter is fitted to the target C distribution; Figure 5 reports forward-modeled ensemble mean changes. The favorable line-of-sight choice (Sec. 2.3, footnote 4) is an explicit modeling assumption that could affect robustness to observational selection, but it is not circular because the modeled quantity is openly defined as the value along that line of sight and is not claimed to be an observer-averaged measure. The paper's self-citations (Becker & Adams 2017; Becker et al. 2020; Livesey & Becker 2024) are background or code references and do not carry the derivation; the secular solution is computed in the paper from Murray & Dermott (1999) via celmech. Thus no load-bearing circular step is present.

Assumptions & free parameters 7 free parameters · 8 assumptions · 0 invented entities

The model rests on standard secular theory plus several constructed inputs: a zero-complexity STIP, a fixed inclination distribution, binary transit detection, and a favorable viewing geometry. No new physical entities are introduced. The central quantities (transit threshold, line of sight) are chosen by hand and not all are reported (R* is missing), which increases the burden on reproducibility and soundness.

free parameters (7)
  • Stellar radius R* = not specified in text
    Sets the transiting inclination threshold I > arctan(R*/a) in Equation 18. Its value determines which planets are counted as transiting, directly affecting the computed gap complexity. The paper does not state R*.
  • STIP planet mass = 1e-5 (star mass = 1)
    Adopted characteristic mass for inner super-Earths/Earths; fixed in all simulations.
  • Innermost STIP semi-major axis a1 = 0.1
    Chosen to define the STIP scale; the authors call the exact distances 'somewhat arbitrary'.
  • Outermost STIP semi-major axis aN = 0.5
    Chosen with a1 to set the radial extent of the STIP; arbitrary.
  • Spacing parameter P (period ratio ratio) = 1
    Taken from the mean observed value of Weiss et al. (2018), yielding zero intrinsic gap complexity by construction.
  • Initial inclination scale (Rayleigh sigma) = 2.5 degrees
    Taken from the empirical Fabrycky et al. (2014) distribution; not varied.
  • Outer giant inclination IOG = 10, 20, 30 degrees
    Sampled over a small grid of discrete values; the results show weak dependence on this parameter.
assumptions (8)
  • domain assumption Second-order Laplace-Lagrange secular theory accurately describes the inclination evolution of the STIP plus outer giant system.
    Used throughout Section 2; the theory assumes well-separated planets, no mean-motion resonances, and no eccentricity-inclination coupling. The authors validate against N-body simulations only in a limited regime (Section 2.4).
  • domain assumption The stellar mass is much larger than all planet masses, so astrocentric coordinates and the given secular matrix are valid.
    Stated at start of Section 2.1; standard for planetary systems but not perfectly satisfied for very massive OGs (mOG/m* up to 0.5 in the grid).
  • domain assumption All planets have zero eccentricity and are initially nodally aligned (Omega_j,0 = 0).
    Assumed in Section 2.3; this removes eccentricity dynamics and sets the line of nodes, simplifying the geometry.
  • domain assumption The initial inclinations of STIP planets follow a Rayleigh distribution with scale 2.5 degrees.
    Sampled as in Section 2.3 from Fabrycky et al. (2014); the results could depend on this choice.
  • ad hoc to paper The STIP planets are arranged with period ratios following P = 1 exactly, so the true gap complexity is zero.
    Constructed in Section 2.3 (Eq. 15) to isolate the secular effect on the observed gap complexity; real systems have nonzero intrinsic gap complexity.
  • ad hoc to paper The observed gap complexity is evaluated along a line of sight orthogonal to the line of nodes and in the mean inclination plane of the STIP.
    Chosen in Section 2.3 as the most favorable geometry for detecting the system as multi-planet; not representative of a random observer.
  • ad hoc to paper Time-averaged gap complexity over a single system's secular evolution approximates the snapshot distribution across a population of systems.
    Argued in Section 3 to connect model outputs to the He & Weiss (2023) sample; relies on an ergodic-like assumption that is not tested.
  • domain assumption A planet is considered transiting if and only if its inclination is below arctan(R*/a); detection completeness is binary.
    Used to identify transiting planets in Section 2.3; real transit surveys have probabilistic detection windows.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Secular Perturbations from Exterior Giants Strongly Influence Gap Complexity in Peas-in-a-Pod Exoplanetary Systems." pith.science (2026). https://pith.science/paper/G6KWRCJO

@misc{pith2026241218661,
  author       = {Pith},
  title        = {Pith review of: Secular Perturbations from Exterior Giants Strongly Influence Gap Complexity in Peas-in-a-Pod Exoplanetary Systems},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/G6KWRCJO}},
  note         = {Machine review of arXiv:2412.18661}
}
read the original abstract

It has been demonstrated that systems of tightly packed inner planets with giant exterior companions tend to have less regular orbital spacings than those without such companions. We investigate whether this observed increase in the gap complexity of the inner systems can be explained solely as the result of secular dynamics caused by the disturbing potential of the exterior companions. Amplification of mutual orbital inclinations in the inner system due to such secular dynamics may lead to the inner system attaining non-mutually transiting geometries, thereby creating artificial observed gaps that result in a higher calculated gap complexity. Using second-order secular theory, we compute time-averaged observed gap complexities along a favorable line of sight for a set of hypothetical systems, both with and without an outer giant. We find that these secular interactions can significantly contribute to the observed gap complexity dichotomy in tightly packed multiple-planet systems.

Figures

Figures reproduced from arXiv: 2412.18661 by the authors.

Figure 1
Figure 1. Factor by which we scale the secular matrix elements when moving or changing the mass of the outer companion. Overlain are KGPS systems from the He & Weiss (2023) analysis containing outer companions and at least three inner planets; cyan triangles denote OG systems while olive triangles denote SC systems. The white stars indicate the averages of these two groups. On average, the scaling factor is ∼ 102 times greate… view at source ↗
Figure 2
Figure 2. Illustration of the dependence of our systems’ architecture on the STIP multiplicity. The vertical lines in￾dicate the fixed values of a1 and aN . Distances are not to scale. Top: The N = 4 case. Bottom: The N = 5 case. a G dwarf. The initial inclinations are sampled from the distribution fit empirically by Fabrycky et al. (2014): Ij,0 ∼ Rayleigh(2.5 ◦ ). (17) We assume zero eccentricity for each body and set them t… view at source ↗
Figure 3
Figure 3. A pair of simulations — one with an exterior companion and one without — of a STIP containing five planets. The companion in this case has a mass of 10−2 , lies at a = 2, and has an inclination of 10◦ relative to the STIP plane. The Laplace–Lagrange solution is computed out to 105 times the shortest dynamical timescale in the system, tdyn (effectively the orbital period of the innermost planet). Note that this plot … view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: Same as [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: Change in ⟨C⟩˜ for a sample of possible system architectures. At each point in these parameter spaces lies a pair of simulations, one of which contains a companion and the other of which does not, that are otherwise identical. Each simulation is run for 109 times the o…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

39 extracted references · 5 canonical work pages

  1. [1]

    Adams, F. C. 2019, MNRAS, 488, 1446, doi: 10.1093/mnras/stz1832

  2. [2]

    C., Batygin, K., Bloch, A

    Adams, F. C., Batygin, K., Bloch, A. M., & Laughlin, G. 2020, MNRAS, 493, 5520, doi: 10.1093/mnras/staa624 Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, ApJ, 935, 167, doi: 10.3847/1538-4357/ac7c74

  3. [3]

    Ballard, S., & Johnson, J. A. 2016, ApJ, 816, 66, doi: 10.3847/0004-637X/816/2/66

  4. [4]

    2020, AJ, 160, 254, doi: 10.3847/1538-3881/abbad3

    Becker, J., Batygin, K., Fabrycky, D., et al. 2020, AJ, 160, 254, doi: 10.3847/1538-3881/abbad3

  5. [5]

    C., & Adams, F

    Becker, J. C., & Adams, F. C. 2016, MNRAS, 455, 2980, doi: 10.1093/mnras/stv2444 —. 2017, MNRAS, 468, 549, doi: 10.1093/mnras/stx461

  6. [6]

    2016, ApJ, 821, 47, doi: 10.3847/0004-637X/821/1/47

    Brakensiek, J., & Ragozzine, D. 2016, ApJ, 821, 47, doi: 10.3847/0004-637X/821/1/47

  7. [7]

    Brefka, L., & Becker, J. C. 2021, AJ, 162, 242, doi: 10.3847/1538-3881/ac2a32

  8. [8]

    L., Knutson, H

    Bryan, M. L., Knutson, H. A., Lee, E. J., et al. 2019, AJ, 157, 52, doi: 10.3847/1538-3881/aaf57f

Show all 39 references
  1. [9]

    L., & Lee, E

    Bryan, M. L., & Lee, E. J. 2024, ApJL, 968, L25, doi: 10.3847/2041-8213/ad5013

  2. [10]

    A., Dressing, C

    Buchhave, L. A., Dressing, C. D., Dumusque, X., et al. 2016, AJ, 152, 160, doi: 10.3847/0004-6256/152/6/160

  3. [11]

    2022, ApJ, 930, 58, doi: 10.3847/1538-4357/ac6024

    Chen, C., Li, G., & Petrovich, C. 2022, ApJ, 930, 58, doi: 10.3847/1538-4357/ac6024

  4. [12]

    C., Lissauer, J

    Fabrycky, D. C., Lissauer, J. J., Ragozzine, D., et al. 2014, ApJ, 790, 146, doi: 10.1088/0004-637X/790/2/146

  5. [13]

    2024, arXiv e-prints, arXiv:2406.09359, doi: 10.48550/arXiv.2406.09359

    Faridani, T., Naoz, S., Li, G., Rice, M., & Inzunza, N. 2024, arXiv e-prints, arXiv:2406.09359, doi: 10.48550/arXiv.2406.09359

  6. [14]

    2024, MNRAS, 527, 79, doi: 10.1093/mnras/stad2962

    Ghosh, T., & Chatterjee, S. 2024, MNRAS, 527, 79, doi: 10.1093/mnras/stad2962

  7. [15]

    J., & Fabrycky, D

    Gilbert, G. J., & Fabrycky, D. C. 2020, AJ, 159, 281, doi: 10.3847/1538-3881/ab8e3c

  8. [16]

    1993, Icarus, 106, 247, doi: 10.1006/icar.1993.1169

    Gladman, B. 1993, Icarus, 106, 247, doi: 10.1006/icar.1993.1169

  9. [17]

    2022, AJ, 163, 201, doi: 10.3847/1538-3881/ac5961

    Goldberg, M., & Batygin, K. 2022, AJ, 163, 201, doi: 10.3847/1538-3881/ac5961

  10. [18]

    2022, AJ, 164, 179, doi: 10.3847/1538-3881/ac8d01

    Hadden, S., & Tamayo, D. 2022, AJ, 164, 179, doi: 10.3847/1538-3881/ac8d01

  11. [19]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

  12. [20]

    Y., & Weiss, L

    He, M. Y., & Weiss, L. M. 2023, AJ, 166, 36, doi: 10.3847/1538-3881/acdd56

  13. [21]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  14. [22]

    P., Ford, E

    Jontof-Hutter, D., Weaver, B. P., Ford, E. B., Lissauer, J. J., & Fabrycky, D. C. 2017, AJ, 153, 227, doi: 10.3847/1538-3881/aa6afd

  15. [23]

    2024, A&A, 687, A121, doi: 10.1051/0004-6361/202349043

    Zhu, Z.-H. 2024, A&A, 687, A121, doi: 10.1051/0004-6361/202349043

  16. [24]

    2023, MNRAS, 525, L66, doi: 10.1093/mnrasl/slad092

    Lammers, C., Hadden, S., & Murray, N. 2023, MNRAS, 525, L66, doi: 10.1093/mnrasl/slad092

  17. [25]

    2020, ApJL, 890, L31, doi: 10.3847/2041-8213/ab72f4

    Li, G., Dai, F., & Becker, J. 2020, ApJL, 890, L31, doi: 10.3847/2041-8213/ab72f4

  18. [26]

    2024, jrlivesey/SecularGapComplexity: v2.0, v2, Zenodo, doi: 10.5281/zenodo.14171612

    Livesey, J., & Becker, J. 2024, jrlivesey/SecularGapComplexity: v2.0, v2, Zenodo, doi: 10.5281/zenodo.14171612

  19. [27]

    2017, ApJL, 849, L33, doi: 10.3847/2041-8213/aa9714

    Millholland, S., Wang, S., & Laughlin, G. 2017, ApJL, 849, L33, doi: 10.3847/2041-8213/aa9714

  20. [28]

    D., & Dermott, S

    Murray, C. D., & Dermott, S. F. 1999, Solar System Dynamics (Cambridge University Press)

  21. [29]

    J., Wyatt, M

    Read, M. J., Wyatt, M. C., & Triaud, A. H. M. J. 2017, MNRAS, 469, 171, doi: 10.1093/mnras/stx798

  22. [30]

    Rein, H., & Liu, S. F. 2012, A&A, 537, A128, doi: 10.1051/0004-6361/201118085

  23. [31]

    2015, MNRAS, 452, 376, doi: 10.1093/mnras/stv1257

    Rein, H., & Tamayo, D. 2015, MNRAS, 452, 376, doi: 10.1093/mnras/stv1257

  24. [32]

    R., Steffen, J

    Rice, D. R., Steffen, J. H., & Vazan, A. 2024, ApJL, 973, L4, doi: 10.3847/2041-8213/ad73db

  25. [33]

    A., Weiss, L

    Thomas, C. A., Weiss, L. M., Isaacson, H., et al. 2024, AJ, 167, 160, doi: 10.3847/1538-3881/ad2840

  26. [34]

    Waskom, M. L. 2021, Journal of Open Source Software, 6, 3021, doi: 10.21105/joss.03021

  27. [35]

    M., Millholland, S

    Weiss, L. M., Millholland, S. C., Petigura, E. A., et al. 2023, in Astronomical Society of the Pacific Conference Series, Vol. 534, Protostars and Planets VII, ed. S. Inutsuka, Y. Aikawa, T. Muto, K. Tomida, & M. Tamura, 863

  28. [36]

    M., Marcy, G

    Weiss, L. M., Marcy, G. W., Petigura, E. A., et al. 2018, AJ, 155, 48, doi: 10.3847/1538-3881/aa9ff6

  29. [37]

    M., Isaacson, H., Howard, A

    Weiss, L. M., Isaacson, H., Howard, A. W., et al. 2024, ApJS, 270, 8, doi: 10.3847/1538-4365/ad0cab

  30. [38]

    1991, AJ, 102, 1528, doi: 10.1086/115978

    Wisdom, J., & Holman, M. 1991, AJ, 102, 1528, doi: 10.1086/115978

  31. [39]

    2018, ApJ, 860, 101, doi: 10.3847/1538-4357/aac6d5

    Zhu, W., Petrovich, C., Wu, Y., Dong, S., & Xie, J. 2018, ApJ, 860, 101, doi: 10.3847/1538-4357/aac6d5

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.