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This paper argues that DESI's DR2 Lyman-alpha forest full-shape analysis passes all pre-defined validation tests for the Alcock-Paczynski measurement, while the growth-rate parameter f-sigma-8 is excluded after mock tests show a persistent

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2026-08-01 07:43 UTC pith:7Y6FPYWD

load-bearing objection A careful, unusually honest validation of the DR2 Lyα AP measurement, with the main caveat being that the N-body cross-check is deferred to an unpublished companion and one caption contradicts the text. the 3 major comments →

arxiv 2607.27411 v1 pith:7Y6FPYWD submitted 2026-07-29 astro-ph.CO

Validation of the DESI DR2 Lyα forest full-shape analysis

M. Herbold , A. Cuceu , P. Martini , H. K. Herrera-Alcantar , J. Guy , C. Gordon , O. Manasoiu , J. Aguilar
show 94 more authors
S. Ahlen O. Alves U. Andrade E. Armengaud S. Avila A. Aviles A. Bault F. Beutler D. Bianchi M. Bonici A. Brodzeller D. Brooks A. Carnero Rosell E. Chaussidon J. Chaves-Montero Z. Chen T. Claybaugh K. S. Dawson A. de la Macorra A. Dey W. Elbers V. A. Fawcett S. Ferraro A. Font-Ribera J. E. Forero-Romero G. Gambardella S. Gontcho A Gontcho D. Gonzalez A. X. Gonzalez-Morales R. Gsponer G. Gutierrez B. Hadzhiyska C. Hahn K. Honscheid D. Huterer M. Ishak S. Jos S. Juneau N. V. Kamble N. G. Kara\c{c}ayl{\i} T. Karim R. Kehoe D. Kirkby F.-S. Kitaura A. Kremin O. Lahav M. Landriau J. Lasker L. Le Guillou A. Leauthaud M. E. Levi Q. Li W. Liu K. Lodha M. Manera A. Meisner R. Miquel J. Morawetz J. Moustakas P. Mukherjee A. Mu\~noz-Guti\'errez S. Nadathur G. Niz H. E. Noriega E. Paillas N. Palanque-Delabrouille J. Pan M. P. Ibanez W. J. Percival F. Prada H. Pulido-Hern\'andez A. P\'erez-Fern\'andez I. P\'erez-R\`afols C. Ravoux J. Rohlf G. Rossi R. Ruggeri M. F. Ruiz-Herrera Bernal L. Samushia E. Sanchez C. Saulder D. Schlegel H. Seo J. Silber F. Sinigaglia M. Siudek G. Tarl\'e W. Turner R. Vaisakh M. Vargas-Maga\~na B. A. Weaver M. Wolfson H. Yang H. Zhang (DESI Collaboration)
This is my paper
classification astro-ph.CO
keywords Lyman-alpha forestAlcock-Paczynski effectbaryon acoustic oscillationsDESI DR2full-shape analysismock validationredshift-space distortionsultraviolet background fluctuations
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper aims to show, before unblinding, that the DESI DR2 Lyman-alpha forest full-shape analysis produces trustworthy cosmological constraints. Using hundreds of mock skies and blinded data, it argues that the BAO peak parameters and the broadband Alcock-Paczynski parameter phi_s are unbiased within one third of the statistical uncertainty, with one notable exception: a 0.6% shift in phi_p that stays inside tolerance. It also argues that the growth-rate parameter f-sigma-8 is too biased to report. If correct, the DR2 Lyman-alpha forest provides a reliable and substantially tighter measurement of cosmic geometry through the Alcock-Paczynski effect than earlier studies. The credibility of the conclusion rests on how faithfully the mocks reproduce the real survey's small-scale and line-of-sight systematics.

Core claim

The paper claims that its validation program, run before unblinding, demonstrates that the DR2 Lyman-alpha forest full-shape analysis recovers unbiased Alcock-Paczynski and BAO parameters. Using a stack of 400 CoLoRe 2LPT mock realizations plus AbacusSummit N-body mock suites, the recovered alpha_p, phi_p, and phi_s all satisfy the pre-set tolerance of one third of the DR2 statistical uncertainty for the chosen scale cuts (r_min = 30 h^-1 Mpc for the auto-correlation, 40 h^-1 Mpc for the cross-correlation). phi_s is consistent with the truth; phi_p shows a 0.6% bias at about 5 sigma that remains within the threshold and is flagged for the systematic error budget. By contrast, f-sigma-8 is bi

What carries the argument

The load-bearing object is the anisotropic Alcock-Paczynski parameter phi = q_perp / q_parallel = D_M H / (D_M H)_fid, split into peak (phi_p) and smooth (phi_s) components, together with the mock-based validation protocol. A stack of 400 CoLoRe 2LPT mock realizations, supplemented by AbacusSummit N-body simulations, is used to calibrate the minimum scale cuts and to establish that any bias above one third of the DR2 statistical uncertainty fails the test. The modeling upgrades doing much of the work are analytic marginalization over the undistorted correlation function below r_min, which removes small-scale continuum-fitting distortions that leak into larger scales, and a scale-dependent UV

Load-bearing premise

The entire validation depends on the simulated mock skies matching the real survey's small-scale and line-of-sight systematics closely enough that analysis choices tuned on mocks remove the same biases in data; the paper itself flags that the mock redshift-error effect is 'possibly overestimated' and un-modeled, and that data uncertainties on f-sigma-8 are about 40% larger than mock uncertainties.

What would settle it

Compare the real DR2 phi_s measurement against the prediction of the DESI DR2 + CMB best-fit cosmological model; a deviation exceeding the combined uncertainty plus the 0.38% validation tolerance would indicate an un-modeled broadband systematic. Alternatively, rerun the mock stack with quasar redshift errors propagated through continuum fitting, which the baseline mocks omit, and check whether phi_s shifts by more than one third of the statistical uncertainty.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • The DR2 Lyman-alpha forest full-shape measurements can be used for cosmological interpretation of the Alcock-Paczynski geometry, combining phi_s and phi_p into a single AP parameter.
  • The f-sigma-8 measurement is not reported for the DR2 Lyman-alpha full-shape analysis; future analyses must either resolve the modeling bias or rescope the measurement.
  • The analytic small-scale marginalization and UVB fluctuation model are validated for reuse in subsequent data releases and Lyman-alpha full-shape analyses.
  • The BAO peak parameters remain stable under the full suite of analysis variations, cross-checking the separate DR2 BAO analysis.
  • The ~0.6% bias in phi_p, while within tolerance, must enter the systematic error budget for the combined AP constraint.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • An implication the authors leave implicit: the ~0.6% bias in phi_p, though inside the validation tolerance, is significant at about 5 sigma, so the combined AP parameter built from phi_s and phi_p should carry a dedicated anisotropic systematic error rather than the isotropic one used in the BAO analysis.
  • Because the mock redshift-error effect is 'possibly overestimated' and not modeled in the baseline, the paper's ~7% f-sigma-8 shift from that effect is an upper bound; if the true effect is smaller, the remaining f-sigma-8 bias becomes harder to explain, while if the mock treatment is wrong in the other direction, the AP validation could be less secure than presented.
  • A testable extension: regenerate the mock suite with redshift errors propagated into continuum fitting and with explicit UVB fluctuations, then check whether the phi_s tolerance of one-third the statistical uncertainty still holds and whether the f-sigma-8 bias drops.
  • The ~40% gap between data and mock uncertainties for f-sigma-8 suggests the mocks do not capture all variance in the real survey; on the authors' own logic, a systematic missing from the mocks could also bias phi_s, so agreement of the final AP measurement with external cosmological constraints would be a corroborating check.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 4 minor

Summary. This paper reports the validation campaign for the DESI DR2 Lyman-α forest full-shape analysis, performed prior to unblinding. The analysis fits the Lyα auto-correlation and Lyα-QSO cross-correlation functions, separating BAO peak parameters (αp, φp) from broadband smooth parameters (αs, φs), and jointly constrains fσ8. The validation uses 400 CoLoRe 2LPT mock realizations (stacked and individually), blinded DR2 data, data splits, and a large suite of analysis and modeling variations, with pre-defined tolerance thresholds of one-third of the statistical uncertainty. The paper concludes that the BAO and AP parameters pass all validation requirements and are stable, while fσ8 is de-scoped because mock studies show a ~10% bias at high significance.

Significance. If the validation claims hold, the paper supports a substantially improved broadband Alcock-Paczynski measurement from the Lyα forest, going beyond BAO-only information, and an honest exclusion of an unreliable fσ8 measurement. The strengths of the paper are the pre-registered validation thresholds, the large mock ensemble, the blinded data protocol, the population-level pull tests, and the explicit de-scoping of fσ8 when mock validation fails. The main risk is that the central AP claim rests on mock fidelity, and the one fully non-linear mock cross-check (AbacusSummit) is not actually presented in this paper.

major comments (3)
  1. [§IVB, §IVA] The AbacusSummit N-body validation is invoked in the abstract and in §IVB as being 'broadly consistent,' but no quantitative results are shown; the text defers details to the unpublished Key Paper [13]. This is a load-bearing issue because the analytic small-scale marginalization and the adopted rmin cuts (§IIID) are the key innovations that enable the broadband φs measurement, and the CoLoRe 2LPT mocks use an approximate perturbative density field. The fully non-linear check is therefore the natural guard against the main known limitation of the primary mock suite. The paper should either include the stacked AbacusSummit results for φs, αp, and φp at the baseline scale cuts (bias, uncertainty, and threshold comparison) or explicitly state that the headline AP validation is conditional on the companion paper.
  2. [§IVA footnote 1, §IVC] The fidelity of the mocks for line-of-sight systematics is directly questioned by the manuscript itself. Footnote 1 states that the mock redshift-error effect is 'possibly overestimated' and 'currently un-modeled'; the resulting AP shifts are within threshold, but the fσ8 shift is ~7%. More importantly, §IVC (Figure 5) shows that the data uncertainty on fσ8 is ~40% larger than the mock uncertainties, which the authors interpret as possible evidence that the mocks are not fully representative. While this does not by itself invalidate φs, it directly weakens the premise that the mocks reproduce the small-scale and line-of-sight systematics relevant to the broadband anisotropy. Please provide a concrete test or quantitative argument that these known mock-data mismatches cannot bias φs at the 1/3σ level—for example, by injecting the redshift-error effect over its estimated plausible range an
  3. [§IVB, §VI, Figure 4] The stacked CoLoRe 2LPT mocks show a 0.6% bias in φp at ~5σ significance. The paper states that this is within the pre-defined one-third threshold, but the final full-shape AP parameter is obtained by combining φs and φp, as stated in §VI. Since the abstract's central claim is that 'the BAO and AP parameters satisfy all validation requirements,' the paper should quantify the resulting bias in the combined parameter φf and show that it remains within tolerance once the φp systematic is propagated, or should explicitly assign the corresponding systematic uncertainty. Deferring this entirely to [13] leaves the validation paper's headline claim incomplete with respect to the parameter that will actually be used for cosmology.
minor comments (4)
  1. [Figure 4 and §IVB] The Figure 4 caption says the baseline results 'show a ~0.5σ deviation in fσ8 relative to the truth,' while §IVB states that fσ8 displays a 10% bias at ≫5σ significance. This is a direct inconsistency and should be corrected (presumably '5σ'). The caption also refers to 'gray dotted contours' as the 1/3σ threshold, while the text refers to the 'black dotted contour'; please make the notation consistent.
  2. [§VI, §VB1] The one validation variation that exceeded the nominal threshold, Δλ=2.4Å, is investigated and attributed to a statistical fluctuation at ~2.7–2.8σ, with a ~10% probability given 19 tests. This is a reasonable interpretation, but the trial factor is applied post hoc. Consider reporting the look-elsewhere-corrected significance, and clarify whether the 0.68% shift is in the same units as the 0.0038 tolerance.
  3. [§VI] The sentence 'we do not present the validation test results on blinded data with φs in §VB, as was done in the DR1 full-shape analysis' is confusing because §VB does present φs shifts for blinded data. It appears the intended meaning is that the fσ8 blinded-data plots are relegated to Appendix C; please rephrase.
  4. [Figures 13–14] The captions refer to the 'growth rate parameter (f)' while the text consistently uses fσ8. Since the model actually constrains fσ8, the figure labels should match the text to avoid confusion.

Circularity Check

0 steps flagged

No circularity: the AP/BAO validation is empirical against independent mocks and blinded data; deferrals to companion papers are evidence gaps, not definitional reductions.

full rationale

The central claim—that the DR2 Lyα full-shape BAO and AP parameters satisfy validation requirements—is supported by end-to-end fits to 400 CoLoRe 2LPT mocks with known input cosmology, by blinded data-split and analysis-variation tests, and by population-level pull and uncertainty checks. No target parameter (α_p, φ_p, φ_s, fσ8) is defined in terms of the mock outcomes, and no fitted quantity is relabeled as a prediction. The r_min scale cuts are selected by requiring mock biases to lie below an externally defined 1/3-σ data-uncertainty threshold; this is a calibration step, and the later demonstration that the adopted cuts pass that threshold is partly by construction, but the paper's substantive claims about stability on blinded data do not reduce to that selection. The fσ8 de-scoping is itself an honest response to a mock-identified bias rather than a circular justification. Self-citations to the companion Key Paper [13] and mock-validation paper [84] are present, and the AbacusSummit cross-check is deferred to [13], but the CoLoRe validation and blinded-data tests presented here independently support the main conclusion; these deferrals concern completeness of evidence, not definitional circularity. Footnote 1 (mock redshift errors 'possibly overestimated' and 'currently un-modeled') and §IVC (data fσ8 uncertainty ~40% larger than mocks) are candid limitations on mock fidelity—a correctness/robustness risk—not a sign that the derivation is equivalent to its inputs.

Axiom & Free-Parameter Ledger

5 free parameters · 5 axioms · 0 invented entities

The paper introduces no new physical entities. Its free parameters are standard nuisance and analysis-choice parameters, plus the newly introduced UVB response parameter. The most important assumptions are the fidelity of the mocks and the accuracy of the distortion-matrix approximation, both of which the paper tests but cannot fully guarantee.

free parameters (5)
  • r_min scale cuts = 30 h^-1 Mpc (auto), 40 h^-1 Mpc (cross)
    Chosen from mock scans as the smallest r_min where recovered parameters stay within 1/3 sigma of the data uncertainty (Section IVB). This hand-set analysis choice directly affects the central AP result.
  • Arinyo small-scale nonlinear correction parameters = q1=0.303, q2=0.267, k_nu=0.576, a_nu=0.443, b_nu=1.66, k_p=11.062
    Fixed, not fitted, to values calibrated on ForestFlow simulations and DESI DR1 P1D (Section IIIE). The central AP result is tested against freeing these parameters (Section VB3).
  • UVB response parameter = free (other UVB quantities fixed to fiducial)
    Introduced in Section IIID to model ultraviolet background fluctuations; free in the baseline fit with the remaining UVB quantities fixed to fiducial values.
  • Metal RSD parameter (mock-only) = best-fit from stacked mocks, then fixed in individual mock fits
    Added in Section IVB to handle metal contamination in CoLoRe 2LPT mocks; fixed to the stack best-fit value for the population tests in Section IVC.
  • Standard nuisance parameters (Ly-alpha bias, beta, QSO bias, beta, HCD parameters, metal amplitudes) = not listed; constrained with Gaussian priors
    Inherited from the DR2 BAO analysis (Section IIIE). The AP parameters are marginalized over these, and the paper shows sensitivity to the beta_HCD prior (Section VB3, Section VI).
axioms (5)
  • domain assumption The CoLoRe 2LPT and AbacusSummit mocks reproduce the relevant Ly-alpha forest and quasar clustering, including contaminants, to the accuracy required by the 1/3-sigma threshold.
    The entire validation program (Section IV) rests on mock fidelity. The paper itself notes redshift-error effects may be overestimated (footnote 1) and that f-sigma-8 data uncertainties are ~40% larger than mock uncertainties (Section IVC), indicating the mocks may not be fully representative.
  • domain assumption The distortion matrix computed with 1% of Ly-alpha pixels is a sufficient approximation.
    Section IIIB states 'we use only a fraction (1%) of the Ly-alpha pixels as an approximation'. This is tested with a 2% sample in Section VB2, but the approximation is load-bearing for the continuum-distortion correction.
  • domain assumption Analytic marginalization over undistorted small-scale modes removes continuum-fitting distortion without biasing parameters or losing constraining power.
    Section IIID and Section IVB: this is a new method central to the scale-cut validation. It is validated on mocks, but its transfer to data is an assumption.
  • domain assumption The Gaussian likelihood and the HEALPix subsampling covariance accurately describe the data.
    Section IIIE reports chi^2/dof=1.011 and a residual normality check (Figure 1), but the covariance is estimated from regional scatter with smoothing, which is an approximation.
  • domain assumption Arinyo small-scale correction parameters calibrated on ForestFlow and DESI DR1 P1D apply to DR2 data.
    Section IIIE fixes these parameters to external calibrations; robustness is tested by freeing them (Section VB3), but the central result depends on this calibration being adequate.

pith-pipeline@v1.3.0-daily-deepseek · 34177 in / 10818 out tokens · 114908 ms · 2026-08-01T07:43:47.167861+00:00 · methodology

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read the original abstract

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$\alpha$ (Ly$\alpha$) forest full-shape analysis. This analysis combines three-dimensional Ly$\alpha$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$\alpha$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$ $h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $f\sigma_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$\alpha$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$\alpha$ forest studies.

Figures

Figures reproduced from arXiv: 2607.27411 by A. Aviles, A. Bault, A. Brodzeller, A. Carnero Rosell, A. Cuceu, A. de la Macorra, A. Dey, A. Font-Ribera, A. Kremin, A. Leauthaud, A. Meisner, A. Mu\~noz-Guti\'errez, A. P\'erez-Fern\'andez, A. X. Gonzalez-Morales, B. A. Weaver, B. Hadzhiyska, C. Gordon, C. Hahn, C. Ravoux, C. Saulder, D. Bianchi, D. Brooks, D. Gonzalez, D. Huterer, D. Kirkby, D. Schlegel, E. Armengaud, E. Chaussidon, E. Paillas, E. Sanchez, F. Beutler, F. Prada, F. Sinigaglia, F.-S. Kitaura, G. Gambardella, G. Gutierrez, G. Niz, G. Rossi, G. Tarl\'e, H. E. Noriega, H. K. Herrera-Alcantar, H. Pulido-Hern\'andez, H. Seo, H. Yang, H. Zhang (DESI Collaboration), I. P\'erez-R\`afols, J. Aguilar, J. Chaves-Montero, J. E. Forero-Romero, J. Guy, J. Lasker, J. Morawetz, J. Moustakas, J. Pan, J. Rohlf, J. Silber, K. Honscheid, K. Lodha, K. S. Dawson, L. Le Guillou, L. Samushia, M. Bonici, M. E. Levi, M. F. Ruiz-Herrera Bernal, M. Herbold, M. Ishak, M. Landriau, M. Manera, M. P. Ibanez, M. Siudek, M. Vargas-Maga\~na, M. Wolfson, N. G. Kara\c{c}ayl{\i}, N. Palanque-Delabrouille, N. V. Kamble, O. Alves, O. Lahav, O. Manasoiu, P. Martini, P. Mukherjee, Q. Li, R. Gsponer, R. Kehoe, R. Miquel, R. Ruggeri, R. Vaisakh, S. Ahlen, S. Avila, S. Ferraro, S. Gontcho A Gontcho, S. Jos, S. Juneau, S. Nadathur, T. Claybaugh, T. Karim, U. Andrade, V. A. Fawcett, W. Elbers, W. J. Percival, W. Liu, W. Turner, Z. Chen.

Figure 1
Figure 1. Figure 1: FIG. 1. Comparison between the histogram of the distri [PITH_FULL_IMAGE:figures/full_fig_p008_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Broadband AP constraints relative to the truth as a [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Stacks of the four Ly [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Histograms of measurement uncertainties for [PITH_FULL_IMAGE:figures/full_fig_p012_5.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Parameter constraints from a joint analysis of all four [PITH_FULL_IMAGE:figures/full_fig_p012_4.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. Histogram of pull values with respect to the truth [PITH_FULL_IMAGE:figures/full_fig_p013_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: FIG. 8. Full-shape and BAO constraints from the baseline [PITH_FULL_IMAGE:figures/full_fig_p015_8.png] view at source ↗
Figure 7
Figure 7. Figure 7: FIG. 7. Full-shape and BAO constraints from the two [PITH_FULL_IMAGE:figures/full_fig_p015_7.png] view at source ↗
Figure 11
Figure 11. Figure 11: The blue (circle) points in Figure 11 demon [PITH_FULL_IMAGE:figures/full_fig_p017_11.png] view at source ↗
Figure 10
Figure 10. Figure 10: FIG. 10. Shifts in the AP measurement from a set of analysis [PITH_FULL_IMAGE:figures/full_fig_p018_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: FIG. 11. Shifts in the AP measurement from a set of analysis [PITH_FULL_IMAGE:figures/full_fig_p019_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: FIG. 12. Full-shape fit results from a stack of 100 mock cor [PITH_FULL_IMAGE:figures/full_fig_p022_12.png] view at source ↗
Figure 14
Figure 14. Figure 14: In particular, we find that fσ8 is sensitive to changes in the modeling of the smooth anisotropic parameter, αs the quasar radiation strength (proximity effect), and UVB fluctuations. We also find that fσ8 exhibits signif￾icant degeneracies with several model parameters, most notably αs. As discussed previously, αs is largely treated as a nuisance parameter because it is difficult to disentan￾gle from oth… view at source ↗
Figure 14
Figure 14. Figure 14: FIG. 14. Shifts in the growth rate parameter ( [PITH_FULL_IMAGE:figures/full_fig_p023_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: FIG. 15. Shifts in the measurement of BAO peak parameters [PITH_FULL_IMAGE:figures/full_fig_p023_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: FIG. 16. Shifts in the measurement of BAO parameters [PITH_FULL_IMAGE:figures/full_fig_p024_16.png] view at source ↗
Figure 17
Figure 17. Figure 17: FIG. 17. Shifts in the AP measurement from a set of analysis [PITH_FULL_IMAGE:figures/full_fig_p025_17.png] view at source ↗

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Reference graph

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