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The Multiband Imaging Survey for High-Alpha PlanetS (MISHAPS) I: Preliminary Constraints on the Occurrence Rate of Hot Jupiters in 47 Tucanae

T0 review · 4 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

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Pith's one-line read The paper claims that hot Jupiters in 47 Tucanae are at least four times rarer than in the Kepler field, with a combined 95% upper limit of f_HJ < 0.11%.

desk verdict A careful, honest upper-limit paper that strengthens the 47 Tuc hot Jupiter constraint to 0.11%, albeit with uncalibrated second-pass vetting and post-detrending injections keeping the exact number soft. read the letter →

arxiv 2412.09705 v2 pith:MRAFVD6M submitted 2024-12-12 astro-ph.EP astro-ph.GA

Alison L. Crisp (1 , 2) , Jonas Klüter (1) , Marz L. Newman (1) , Matthew T. Penny (1) , Thomas G. Beatty (3) , L. Ilsedore Cleeves (4) , Karen A. Collins (5)
show 24 more authors
Jennifer A. Johnson (2) Marshall C. Johnson (2) Michael B. Lund (6) Clara E. Martínez-Vázquez (7) Melissa K. Ness (8 9) Joseph E. Rodriguez (10) Robert Siverd (11) Daniel J. Stevens (12) Steven Villanueva (13) Carl Ziegler (14) ((1) Louisiana State University (2) The Ohio State University (3) University of Wisconsin (4) University of Virginia (5) Harvard-Smithsonian Center for Astrophysics (6) California Institute of Technology (7) NOIRLab (8) Columbia University (9) Flatiron Institute (10) Michigan State University (11) University of Hawai'i (12) University of Minnesota Duluth (13) NASA Goddard Space Flight Center (14) Stephen F. Austin State University)
This is my paper · ORCID
classification astro-ph.EPastro-ph.GA
keywords ExoplanetastronomyTransitphotometryHotJupitersGlobularstarclusters47TucanaeOccurrencerateDetectionefficiency
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

This paper tries to establish that hot Jupiters are genuinely scarce in the globular cluster 47 Tucanae, not just undetected. Searching 19,930 outer-cluster stars with a wide-field ground-based camera on a 4-meter telescope, the authors find no convincing planets, rule out all 35 transit candidates as false positives without follow-up, and combine their sensitivity with the 2000 Hubble search of 34,091 inner-cluster stars. The resulting 95% upper limit is $f_{\rm HJ} < 0.11\%$ for planets with periods 0.8 to 8.3 days and radii 0.5 to 2.0 Jupiter radii, about four times lower than the hot Jupiter rate measured in the Kepler field. If the limit holds, it constrains how giant planets form in metal-poor, densely packed stellar environments and tests whether enhanced $\alpha$-element abundances can compensate for low iron.

What carries the argument

The central machinery is a single-transit search rather than a phased multi-transit search. A sliding boxcar scans each night's detrended lightcurve for a transit-shaped dip and requires a signal-to-noise ratio of at least 7; the telescope's aperture makes a Jupiter-radius transit detectable over several magnitudes of the cluster main sequence, so even one partial transit can be found. Detection efficiency is calibrated by injecting about 40,000 synthetic transits into the real lightcurves, measuring recovery through the automated search and the first human vetting step, which the paper finds to be near 90% efficient, and folding in the geometric transit probability. The quantity $N_1 = N_\star \times \epsilon_{\rm total}$, the expected number of planets if every star had one, converts a null result into an occurrence limit through $f_{\rm HJ} < 3/N_1$.

What would settle it

An injection-recovery test that adds synthetic transits before detrending and independently audits the second vetting step; if the true recovery fraction falls materially below the paper's measured efficiency, the combined $N_1 = 2719$ and the 0.11% upper limit would be too optimistic.

Watch

Extended reading notes

Core claim

On its own, the new survey's 19,930 stars yield $N_1 = 830$ and a 95% upper limit $f_{\rm HJ} < 0.36\%$ over the same period and radius range as the earlier Hubble search. Because the two surveys cover independent samples, the new one in the cluster's outskirts and Hubble's in the core, their expected yields add, giving $N_1 = 2719$ and a combined limit $f_{\rm HJ} < 0.11\%$ for hot Jupiters with $0.8 \leq P \leq 8.3$ days and $0.5 \leq R \leq 2.0\,R_{\rm Jup}$. The paper argues this is the strongest limit to date and concludes that the occurrence rate of hot Jupiters in 47 Tuc is roughly four times below that of the Kepler field.

Load-bearing premise

That the measured recovery of injected, already-detrended synthetic transits, including the first human vetting pass, equals the real probability that a hot Jupiter transit would have been found, and that the later, unquantified vetting steps do not discard real planets.

Editorial extensions

If this is right

  • If the limit is right, hot Jupiters occur in 47 Tuc at least four times less often than in the Kepler field, making the cluster a genuinely different planet formation environment.
  • The result rules out, at 95% confidence, the occurrence rate expected if the cluster's stars hosted hot Jupiters at the same rate as Kepler stars of similar mass, before metallicity corrections are applied.
  • The quantified human vetting efficiency, near 90% and lower at longer periods, shows that visual inspection cannot be treated as perfect in future transit surveys and must be included in occurrence limits.
  • The $N_1$ framework gives a reusable way to combine independent null searches, as demonstrated by merging the outer-cluster survey with the inner-cluster Hubble search.
  • Extending the survey to the central chips and to fainter stars should push the combined sensitivity toward the predicted alpha-element-enhanced rate, which would require $N_1 \approx 5450$ to rule out.

Reading between the lines

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

  • Because synthetic transits were added after detrending, a signal that detrending would partially erase could make the measured recovery efficiency optimistic; the paper itself flags this as a future fix.
  • If the sensitivity is as claimed, the limit already approaches the occurrence rate predicted when alpha-element abundance rather than iron sets planet formation, about 0.055%, leaving a narrow window to discriminate between the two hypotheses.
  • The single-transit observing strategy, using many short windows instead of continuous coverage, could be applied to other globular clusters or crowded fields where multi-transit searches are impractical.
  • The three newly cataloged detached eclipsing binaries are a byproduct of the search that may serve as independent tracers of the cluster's binary population and dynamics.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 5 minor

Summary. The paper presents the first results of the MISHAPS ground-based survey for transiting hot Jupiters in the globular cluster 47 Tucanae, using ~24 nights of DECam r/z time-series photometry. The authors analyze 19,930 likely cluster members selected by Gaia proper motions and a color-magnitude cut, search for single and partial transits with a boxcar algorithm, and characterize their detection efficiency with ~40,000 injected transits that pass through the algorithmic search and Zooniverse first-pass human vetting. They report no surviving planet candidates, reject 35 initial transit candidates through detailed vetting, identify 4 eclipsing binaries, and derive a 95% upper limit of f_HJ < 0.43% for their survey alone over 0.75-2.0 R_Jup and 0.5-10 days. Combining with the G00 HST survey over the overlapping range 0.8-2.0 R_Jup and 0.5-8.3 days, they quote f_HJ < 0.11%, which they describe as the strongest limit to date and a factor of ~4 below the Kepler-field occurrence rate.

Significance. The survey addresses a genuinely open question: whether hot Jupiter formation is suppressed in the low-metallicity, high-stellar-density environment of a globular cluster. The pipeline is careful and transparent in several respects: injection-recovery simulations are performed over the actual stellar sample; the first-pass human Zooniverse vetting efficiency is explicitly measured rather than assumed to be 100%; proper-motion and color cuts remove foreground and SMC contamination; and the injection-recovery products are publicly released. The 4 new eclipsing binaries are a useful byproduct. However, the central quantitative claim, the combined 0.11% upper limit, depends on two efficiency terms that the paper itself flags as uncalibrated (the second-pass detailed vetting and the post-detrending injection procedure) and on an adopted value of G00's sensitivity that the paper's own Section 8 shows to be sensitive to the assumed planet population. Because both uncalibrated effects act in the same direction, the quoted limit is likely too stringent as a stated 95% confidence bound.

major comments (4)
  1. [Section 8 and Eq. (17)-(22)] The total efficiency used in the N1 calculation includes only the algorithmic detection efficiency and the Zooniverse first-pass approval fraction; the detailed vetting described in Section 6 (target-centered cutout photometry, period searches, stacked difference images) is applied only to the 39 real candidates and never to the injected transits. Section 8 explicitly states that 'the remaining vetting steps we take also are not 100% efficient.' Any real transit rejected in the second pass reduces the true N1 and weakens the upper limit, so the reported f_HJ < 0.11% is biased low. The authors should either calibrate the second-pass efficiency by injecting synthetic transits through that full procedure, or apply and propagate a conservative correction factor (e.g., a range of assumed retention fractions).
  2. [Section 5.1, footnote 19] The transit injections are added after the TFA detrending step, so the computed efficiency does not account for the possibility that TFA partially absorbs real transit signals when they are present in the original lightcurves. The paper acknowledges this in footnote 19 as a future fix. Since this effect also makes the survey appear more sensitive than it actually is, it directly impacts the central upper limit. At minimum, the authors should estimate the size of this effect, for example by injecting before detrending on a subset of lightcurves and comparing the recovered efficiency, or by citing published estimates of TFA's suppression of transit signals.
  3. [Section 7, Eq. (24) and Table 5] The combined limit uses G00's N1 = 1889, derived from G00's expected yield of 17 planets at an assumed 0.8-1.0% occurrence rate. The paper itself notes in Section 8 that MW17's recalibration of G00's sensitivity implies an effective N1 about two-thirds as large, and the authors compute that a reweighted combination gives a combined N1 of 1776 and f_HJ < 0.17% rather than 0.11%. Because the headline claim 'strongest limit to date, factor of ~4 below the Kepler field' depends on the choice of G00's N1, the authors must present the combined limit under both calibrations and either justify the original G00 value as the appropriate one for a uniform period-radius definition or lead with the more conservative value.
  4. [Section 7, Eq. (22) and Eq. (25)] The reported 95% upper limit propagates only Poisson counting statistics (3/N1). Systematic uncertainties in the stellar radius estimates (§3.4.3, which feed the transit-depth and transit-probability calculations), the spline photometric transforms in Table 3 (particularly the ±0.08 mag residual in the (r-z)PS1 to (g-i)PS1 transform), the fixed choice of 15 TFA trend stars (§4.2), and the adopted G00 N1 are not propagated into the final limit. Since the paper's main result is a quantitative bound, the authors should provide a systematic error budget or demonstrate that the limit is robust to these choices; without this, the 0.11% figure is presented with overstated precision.
minor comments (5)
  1. [Abstract and Section 8] The abstract states the limit is 'a factor of ~4 below the occurrence rate in the Kepler field', but Section 8 compares against MW17's 0.18% rate, which would be a factor of 1.6. The factor of ~4 appears to refer to Fressin et al.'s 0.43% rate over a longer period range. The authors should specify which comparison is being made in the abstract to avoid the apparent inconsistency.
  2. [Section 5.1] The paper acknowledges using the same limb-darkening coefficients in z as in r, but leaves the impact unquantified. A sentence estimating the resulting error in transit depth or recovery efficiency would clarify whether this is truly negligible for the reported limits.
  3. [Section 5.4, Eq. (15)] The definition of C_j states that a night counts if the classification is 'partial or full transit unanimously for all users', but with Nuser=2 it is not explicit whether both users must classify the same night as a transit, or whether one user's transit classification plus the other's abstention counts. Please clarify the unanimity rule.
  4. [Figures 22-25] Several figure captions read only 'Same as previous' without identifying which candidates are shown in the figure. The captions should list the candidate IDs so the figures are self-contained.
  5. [Section 6.2.2] The sentence 'The search returns an estimated depth of 0.018 and duration of 1.0 hr for this eclipse for this eclipse' contains a duplicated phrase; also, 'V-shaped bottom' should be introduced as a technical term or placed in quotes.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the occurrence-rate limit is computed from independent injection-recovery simulations and an external HST survey.

full rationale

The central limit f_HJ < 0.11% is obtained as 3/N1 (Eq. 22) with N1 = 2719 = 830 (this survey) + 1889 (G00). The MISHAPS N1 = N_star * epsilon_total is measured from roughly 40,000 injected transits recovered through the boxcar search and blinded Zooniverse first-pass vetting; it is not defined in terms of the occurrence rate it constrains. The G00 sensitivity is imported from an external Hubble survey (G00; reanalyzed by MW17). No equation in the derivation has the target quantity on both sides, and no fitted parameter is renamed as a prediction. The paper's acknowledged limitations (footnote 19: injections are made after detrending; Section 8: later vetting steps are likely not 100% efficient and were not calibrated) affect the accuracy of the measured efficiency, but they do not make the argument circular: the efficiency remains an independently measured input rather than a restatement of the output. Several references include authors of the present paper (Zang et al. 2018 photometric calibration and surface-brightness relations; Siverd et al. 2012 ISIS modification; Johnson et al. 2010 metallicity relation used only in discussion; Collins et al. 2017 AstroImageJ), but none of these is the load-bearing premise of the upper-limit calculation. The central result is therefore self-contained against external data and benchmarks.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

No new physical entities are introduced. The central limit depends on standard Poisson statistics, membership cuts, injection-based efficiency estimates, and external calibration of G00. The most fragile inputs are the unquantified second-pass vetting efficiency and the post-detrending injection scheme, both acknowledged in the text.

free parameters (4)
  • S/N detection threshold = 7
    Chosen from injection tests to pass about 47% of injected transits and reject about 99% of no-transit nights; directly sets epsilon_det and therefore N1.
  • Number of TFA trend stars = 15
    Selected by minimizing a quasi-reduced chi-squared metric on the N10 chip; affects detrending and recovery of shallow transits.
  • ISIS aperture parameters = rad_phot=5.0 px, rad_aper=6.0 px; second pass 10.0 and 11.0 px
    Tuned on a Galactic bulge subset and later increased for target-centered photometry; affects measured depths and detection efficiency.
  • Spline transform coefficients for NSC to PanSTARRS colors = Coefficients, knots, and roots in Table 3
    Fitted to two calibration fields and used to estimate stellar radii, which set transit probabilities and depth-to-radius conversions.
assumptions (6)
  • standard math Poisson statistics with Nexp=3 at 95% confidence is the correct statistical model for the zero-event upper limit.
    Used in Eq. 19 to convert N1 to f_HJ; if detection efficiency is overestimated, the resulting limit is biased.
  • domain assumption Proper motion and color cuts isolate 47 Tuc members from SMC and Milky Way foreground stars.
    Section 3.3; contamination would change the effective stellar sample and the interpretation of the occurrence rate.
  • ad hoc to paper The transit injection into de-trended lightcurves (after TFA) measures the real detection efficiency.
    Acknowledged in Section 5.1 footnote 19 as a limitation; if de-trending removes real transits, epsilon_det is overestimated and the upper limit is too low.
  • ad hoc to paper The human Zooniverse and second-pass vetting steps do not reject real transiting planets.
    Section 5.3 and Section 8: first-pass efficiency is quantified at about 90%, but second-pass efficiency is not; authors state it is likely not 100%.
  • domain assumption G00's N1=1889, derived from their expected yield under an assumed occurrence rate, correctly measures G00's sensitivity.
    Section 7 Eq. 24; this external calibration underpins the combined limit. If G00's assumed detection efficiency is biased, the combined limit changes.
  • domain assumption Stellar radii from the surface brightness relation and the 4.45 kpc distance are accurate.
    Section 3.4; radii set transit probability and depth-to-radius conversion; systematic errors are not propagated into the limit.

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Cite this review

Pith. "Pith review of The Multiband Imaging Survey for High-Alpha PlanetS (MISHAPS) I: Preliminary Constraints on the Occurrence Rate of Hot Jupiters in 47 Tucanae." pith.science (2026). https://pith.science/paper/MRAFVD6M

@misc{pith2026241209705,
  author       = {Pith},
  title        = {Pith review of: The Multiband Imaging Survey for High-Alpha PlanetS (MISHAPS) I: Preliminary Constraints on the Occurrence Rate of Hot Jupiters in 47 Tucanae},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/MRAFVD6M}},
  note         = {Machine review of arXiv:2412.09705}
}
abstract

The first generation of transiting planet searches in globular clusters yielded no detections, and in hindsight, only placed occurrence rate limits slightly higher than the measured occurrence rate in the higher-metallicity Galactic thick disk. To improve these limits, we present the first results of a new wide field search for transiting hot Jupiters in the globular cluster 47~Tucanae. We have observed 47~Tuc as part of the Multiband Imaging Survey for High-Alpha Planets (MISHAPS). Using 24 partial and full nights of observations taken with the Dark Energy Camera on the 4-m Blanco telescope at CTIO, we perform a search on 19,930 stars in the outer regions of the cluster. Though we find no clear planet detections, by combining our result with the upper limit enabled by Gilliland et al.'s 2000 Hubble search for planets around an independent sample of 34,091 stars in the inner cluster, we place the strongest limit to date on hot Jupiters with periods of $0.8 \leq P \leq 8.3$ days and $0.5~R_{\rm Jup} \leq R_{\rm P} \leq 2.0~R_{\rm Jup}$ of $f_{\rm HJ} < 0.11\%$, a factor of ${\sim}$4 below the occurrence rate in the \textit{Kepler} field. Our search found 35 transiting planet candidates, though we are ultimately able to rule out each without follow-up observations. We also found 4 eclipsing binaries, including 3 previously-uncataloged detached eclipsing binary stars.

Figures

Figures reproduced from arXiv: 2412.09705 by the authors.

Figure 1
Figure 1. We make an initial wide selection of potential cluster members, using the mean proper motion values for 47 Tuc in H. Baumgardt et al. (2019), ¯µα = 5.25 mas/yr and ¯µδ = −2.53 mas/yr and a selection radius of p (µα − µ¯α) 2 + (µδ − µ¯δ) 2 < 3σ, (1) where σ=0.94. Using the initial selection, we compute new values of ¯µα, ¯µδ, and their corresponding errors by averaging over the Gaia DR3 values for the selection. We m… view at source ↗
Figure 2
Figure 2. r vs. (r−z) color-magnitude diagram of our field, with only the DoPHOT type cut applied (black). Our final selection of stars is overplotted in red, and the proper mo￾tion-selected SMC stars (selected using the same procedure as for 47 Tuc stars) are overplotted in gold. The remain￾ing black points are targets which either lie outside the 3-σ 47 Tuc and SMC proper motion selections, or have no Gaia matches. 3.4.1. E… view at source ↗
Figure 3
Figure 3. Transformation plots to transform our data from NSC magnitudes to PS1 magnitudes (top row), and between PS1 magnitudes (bottom row). The CMDs of the datasets used to calculate the transforms are shown in black points. The functions generated by the spline fits are shown with the solid red lines in the upper panels. The binned medians of the fit data are shown with the dashed blue lines. The knots of the splines are … view at source ↗
Figures from the paper (21 more)
Figure 4
Figure 4. Figure 4: Radius estimation results. Top panel: The resul￾tant radius estimates of our full field vs. r magnitude, with our final stellar selection highlighted in red. The radii for a MIST isochrone calculated for the PanSTARRS photometric system are given by the gold line. Bott…
Figure 5
Figure 5. Figure 5: Scaled median absolute deviation (MAD, a robust estimate of RMS) of lightcurve photometry in our observa￾tions of 19,930 47 Tuc stars compared to the transit depths of planets orbiting 47 Tuc stars. Data from bad nights are re￾moved prior to calculating this statistic.…
Figure 6
Figure 6. Figure 6: Example of injected full and partial transits of a 1.26RJup planet orbiting a 0.59R⊙, r = 19.9 star in our data with P=0.97 days. Each panel shows a different night, with the top two panels showing nights flagged as having full transits, and the bottom two showing nigh…
Figure 7
Figure 7. Figure 7: Histogram showing the S/N of nights with (yel￾low) and without (blue) injected transits. The dotted red line indicates our chosen S/N≥ 7 threshold. The solid and dashed black lines represent the probability of a lightcurve containing a detection of a given S/N for nigh…
Figure 8
Figure 8. Figure 8: Simplified version of the MISHAPS lightcurve classification workflow. The rightmost panel shows the tools users are given, while the rest show individual nights of the lightcurve. A blue panel indicates a full transit as flagged by the search algorithm, a gray panel in…
Figure 9
Figure 9. Figure 9: Efficiencies of our transit search and Zooniverse vetting, binned as a function of planet radius Rp (top left), orbital period P (top right), r−magnitude (bottom left), and impact parameter b (bottom right). The blue-triangle lines show our detection efficiency ϵdet, t…
Figure 10
Figure 10. Figure 10: 2D plots of detection efficiencies of our pipeline, estimated in bins of Rp and P. The top panel shows ϵdet for the search algorithm, and middle panel shows ϵZoo for the Zooniverse vetting, and the bottom panel shows the overall efficiency incorporating the transit pr…
Figure 12
Figure 12. Figure 12: Example of a candidate rejected for a clear blend. The lightcurve of the detection is plotted on the left with the search’s model. The stacked in-transit difference image and reference image are shown in the middle and right panels, respectively. Though the lightcurve…
Figure 13
Figure 13. Figure 13: r−band lightcurves from survey night 1225 for MISHAPS F47T S9 01005029 (left), MISHAPS F47T S10 01006025 (middle), and MISHAPS F47T S10 01010875 (right). The de-trended lightcurves are plotted in teal circles, and the target-cen￾tered lightcurves are plotted in purple…
Figure 14
Figure 14. Figure 14: CMD for our field (black points) with our tar￾gets (red points) and candidates highlighted. The rejected candidates are given by the blue circles, and the EBs are given by the yellow squares. periods, which, if the single transit-like signals were pe￾riodic and detect…
Figure 16
Figure 16. Figure 16: Top row: Transit search lightcurve plot for MISHAPS F47T S11 01004730 from night 1403 showing a S/N = 8.7 detection. The images in the middle and right of the row are the in-transit stacked difference image and the reference image. Middle: Detrended (blue) and target–…
Figure 17
Figure 17. Figure 17: Lightcurves and stacked in-eclipse difference im￾ages for EB candidates. The lightcurves of each detection are shown in the left column, with the r−band data plotted in blue, and the z−band data plotted in red. The middle col￾umn shows the stacked in-eclipse differenc…
Figure 18
Figure 18. Figure 18: 2D occurrence rate upper limits, estimated in bins of Rp and P. The labels on each bin give the occurrence rate in percent. To enable more detailed comparisons with future work, we provide with this article the results of our [PITH_FULL_IMAGE:figures/full_fig_p024_18.png]
Figure 19
Figure 19. Figure 19: Examples of injected transits that pass our S/N=7 detection threshold, spanning the range of Rp and P that we explore. Each plot falls within one of our P and Rp bins, with binned P increasing from left to right and binned Rp increasing from bottom to top. The bin edg…
Figure 20
Figure 20. Figure 20: Examples of injected full transits that pass our S/N=7 detection threshold, spanning the range of Rp and r that we explore. Each plot falls within one of our r and Rp bins, with binned r increasing from left to right and binned Rp increasing from bottom to top. The bi…
Figure 21
Figure 21. Figure 21: Examples of injected partial transits that pass our S/N=7 detection threshold, spanning the range of Rp and r that we explore. Each plot falls within one of our r and Rp bins, with binned r increasing from left to right and binned Rp increasing from bottom to top. The…
Figure 22
Figure 22. Figure 22: Detection lightcurves (left column), stacked in-transit difference images (middle column), and r−band reference im￾ages (right column) for rejected candidates N5 01007377, N9 01001945, N9 01002359, N9 01005409, N9 01010459. N9 01012179, N10 01021994, N17 01009501, S2 …
Figure 23
Figure 23. Figure 23: Same as previous, for rejected candidates S10 01010875, S10 01011133, S10 01012927, S10 01010875, S10 01020146, S11 01004730, S15 01005434, S16 01000575, S16 01001403, and S31 01003863 [PITH_FULL_IMAGE:figures/full_fig_p036_23.png]
Figure 24
Figure 24. Figure 24: Same as previous, for rejected candidates N10 01015356, N10 01016157, N10 01018928, N15 01005656, S5 01001384, S10 01008184, S10 01011503, and S10 01013998 [PITH_FULL_IMAGE:figures/full_fig_p037_24.png]
Figure 25
Figure 25. Figure 25: Same as previous, for rejected candidates S2 01002825 and S16 01009327 [PITH_FULL_IMAGE:figures/full_fig_p038_25.png]
Figure 26
Figure 26. Figure 26: Same as previous, for rejected candidates N11 01005644 and N9 01005022 [PITH_FULL_IMAGE:figures/full_fig_p039_26.png]

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