Turbulent dynamo in the terrestrial magnetosheath.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓Reported values are derivable from the shared data
- ✓The central claim held under reproduction
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡The deviation was non-trivial in magnitude
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
Described well enough -> PARTIAL 1:1 reproduction. Zenodo CodesData.zip ships, per figure, the authors' MATLAB plotting scripts + .mat files holding the ALREADY-DERIVED quantities as irfu-matlab TSeries/EpochTT objects (the heavy MMS->derived step is done by the authors, not shipped as a runnable pipeline). Reproduced the headline scalar results WITHOUT MATLAB by writing a custom MATLAB-v7 MCOS decoder (analog of the v7.3 decoder from pmid-35105885) to read the TSeries data + TT2000 epochs, on «our HPC». Epoch->UTC lands exactly on the paper's 2015-11-30 00:21:44-00:26:43 UT interval. C1 Eq.1 balance reproduces EXACTLY (r=1.0) but is an algebraic identity encoded in the data, not an independent empirical agreement (flagged for auditor). C2 length-scale anisotropy 37-44 vs reported 40+/-20 (within tol). C5 Case I dynamo excursion -6.13 vs -6+/-0.7 (within tol). C6 Case II fall -8.33 vs -9+/-0.9 (within tol) but rise +4.79 vs +6+/-0.5 below tol (boundary-sensitive). NOT attempted: raw MMS CDF->TSeries re-derivation (c_4_grad etc.), gyroradii (need raw FPI moments; flagged 95 km paper vs 99 km script discrepancy), Pm scaling estimate, pitch-angle spectrograms (MATLAB-only) -- the hard ~20%. No fabrication detected; one internal 95-vs-99 km annotation inconsistency and the Eq.1-as-identity caveat noted.
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Assessment versions
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v1 current initial assessment Score 70assessed: 2026-06-14 ⛓ 989e4a66ec9c
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Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-14
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: opusThe authors test whether a turbulent small-scale dynamo (SSD) operates in the terrestrial magnetosheath, asking if high-resolution multi-point MMS observations capture the predicted dynamo signatures—stretched-folded magnetic field topology and pressure-anisotropy instabilities that amplify magnetic fields in collisionless plasma turbulence.
- ★ Evidence for a turbulent small-scale dynamo is present in the terrestrial magnetosheath, captured by high-resolution MMS observations. finding
- ★ The predicted stretched-and-folded magnetic field topology arises naturally in magnetosheath turbulence, shown by anticorrelation between magnetic field magnitude and field line curvature. finding
- ★ Pressure-anisotropy instabilities (mirror and firehose) that break adiabatic invariance and enable field amplification are abundant in the magnetosheath. mechanism
- ★ Magnetic field changes (d lnB/dt) can be evaluated in-situ from the magnetic induction equation using only the stretching (bb:∇Vi) and compression (−∇·Vi) terms computable from multi-point data. method
- ★ A large magnetic Prandtl number regime (Pm ≫ 1) indicates the plasma behaves as a viscous-scale 'stretch-and-fold' dynamo even without frequent collisions. mechanism
- ★ Earth's magnetosheath can serve as a natural testbed/laboratory for validating dynamo theories and simulations. resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Multi-point in-situ magnetic field measurements (tetrahedron gradient estimation) | terrestrial magnetosheath plasma (Earth) | none (natural observation) | magnetic field magnitude/components and spatial gradients (bb:∇Vi, −∇·Vi, d lnB/dt) | Magnetospheric Multiscale (MMS) mission, 4 spacecraft (MMS1-4) |
| In-situ ion velocity / plasma moment measurements | terrestrial magnetosheath plasma (Earth) | none | ion velocity (150 ms cadence), plasma beta, anisotropic ion temperatures | MMS plasma instruments (GSE coordinates) |
| Magnetic field curvature / characteristic wavenumber analysis | terrestrial magnetosheath (tetrahedron barycenter) | none | field line curvature K, parallel/perpendicular length scales l∣∣ and l⊥ | MMS tetrahedron (separations <20 km) |
- ▼ Anticorrelation between normalized squared magnetic field magnitude and normalized field line curvature, consistent with stretched-folded geometry.
- – Ratio of parallel to perpendicular magnetic length scales l∣∣/l⊥ measured for the interval. 40 ± 20
- ▲ Inferred magnetic Prandtl number range from length-scale ratio, indicating Pm ≫ 1 stretch-and-fold dynamo regime. Pm ∈ (400, 3600)
- – Pressure-anisotropy points exceed mirror (Ti⊥/Ti∣∣ > 1) and firehose (Ti⊥/Ti∣∣ < 1) instability thresholds, with subintervals I1 (firehose) and I2 (mirror) identified.
- – Positive stretching term and negative compression (converging flows) lead to magnetic field growth; opposite signs to field decrease.
- – Spacecraft sampled convected plasma volume over ~40,000 km along-trajectory extent during the interval. ~40,000 km
- other l∣∣/l⊥ = 40 ± 20 (ratio of parallel to perpendicular magnetic length scales)
- other Pm ∈ (400, 3600) (inferred magnetic Prandtl number range)
- mean 95 ± 84 km (average ± standard deviation of ion gyroradius)
- mean 0.9 ± 0.63 km (average ± standard deviation of electron gyroradius)
- other <20 km (MMS inter-spacecraft separation (sub-ion, near-electron scales))
- other 150 ms (ion velocity measurement cadence)
- other β ≫ 1 (typically β ≳ 1) (plasma beta in magnetosheath promoting instabilities)
- other 200 km s−1 (assumed convection speed; interval >4 min on 2015-11-30 00:21:45–00:26:43 UT)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The paper presents observational evidence for turbulent small-scale dynamo action in the terrestrial magnetosheath using ~4 minutes of high-resolution four-spacecraft MMS data from 2015-11-30. The statistical approach is primarily descriptive: physical quantities derived from multi-point spacecraft gradient estimates (dynamo terms, magnetic curvature, pressure anisotropy, characteristic length scales) are visualized as 2D scatter/histogram plots and compared against deterministic theoretical instability thresholds. Results are reported for the full interval alongside two representative case-study subintervals; dispersion is conveyed as mean ± standard deviation and rms normalization, with no formal inferential hypothesis tests.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| 2D histogram / scatter anticorrelation analysis (no formal test statistic reported) | Normalized squared magnetic field magnitude vs. normalized magnetic field curvature (Fig. 2a); color-coded by number of points per bin | All data points from the single ~4-minute interval across 4 spacecraft; exact n not stated | not stated |
| Comparison of measured β_i∥ vs T_i⊥/T_i∥ against theoretical instability growth-rate threshold curves | Pressure-anisotropy instability diagram (Fig. 2b); mirror-mode and firehose thresholds from refs 33–35 | MMS1–4 time series from the ~4-minute interval; exact n not stated | not stated |
| Scatter plot distribution with mean ± SD summary | Perpendicular vs. parallel magnetic length scales l⊥ and l∥ (Fig. 2c); average ion and electron gyroradii reported as mean ± SD | — | not stated |
| Signed scatter plot comparison of dynamo terms | Stretching (bb:∇V_i) and compression (−∇·V_i) terms vs. d ln B/dt (Fig. 2d) | — | not stated |
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The anticorrelation between magnetic field magnitude and curvature (Fig. 2a) is shown as a 2D scatter/histogram without a quantitative correlation coefficient↳ Could also: A Spearman rank correlation coefficient (ρ) with a bootstrap 95% confidence interval could also be reported alongside the scatter plot — A numerical correlation coefficient enables direct quantitative comparison with dynamo and turbulence simulations that report the same anticorrelation, and a CI conveys the precision of the estimate from the available data
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Physical quantities (gyroradii, l∥/l⊥) are summarized with mean ± SD; standard deviations are large relative to the means (e.g., ion gyroradius SD ≈ 88% of mean), suggesting skewed distributions↳ Could also: Median with interquartile range (IQR) or a log-normal characterization could also be reported for heavily skewed turbulence data — For the heavy-tailed or skewed distributions typical of turbulent plasma parameters, the median and IQR are more robust location and spread estimates than the mean and SD
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The study is based on a single, selected ~4-minute event interval↳ Could also: A statistical survey across multiple magnetosheath intervals meeting pre-defined selection criteria could also be conducted — A multi-event survey would allow estimation of how frequently the reported dynamo signatures occur and whether the selected interval is representative, extending the generalizability of the findings
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The proportion of data points falling in pressure-anisotropy unstable regions (Fig. 2b) is not quantified↳ Could also: The fraction of points beyond each instability threshold, with a bootstrap confidence interval, could also be reported — Quantifying the prevalence of instability-unstable states as a reproducible percentage provides a metric directly comparable across different intervals, missions, or simulations
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Case-study subintervals I1 and I2 are highlighted as representative examples without a stated objective selection criterion↳ Could also: Pre-specified quantitative selection criteria (e.g., intervals where |d ln B/dt| exceeds a defined threshold) could also be used to identify representative subintervals — Objective, pre-specified criteria make case-study selection reproducible and reduce the potential for confirmation bias in illustrative example choice
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Correlation between measured magnetic field/velocity fluctuations and the computed dynamo terms is described qualitatively ('strongly correlated') for the highlighted subintervals↳ Could also: A cross-correlation function or Pearson/Spearman coefficient with lag analysis could also be computed to quantify the degree of correspondence between the measured and modeled fluctuations — A quantitative correlation measure with uncertainty bounds would allow assessment of how well the kinematic dynamo model captures the observed fluctuation structure across different subintervals
Citation network
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What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-41708617
Paper: Vörös Z. et al., "Turbulent dynamo in the terrestrial magnetosheath", Nat Commun 2026. PMID 41708617 · PMCID PMC13032041 · DOI 10.1038/s41467-026-69469-y. Manuscript ref NCOMMS-25-30764A.
Code: irfu-matlab (https://github.com/irfu/irfu-matlab, also zenodo:11550090) — a third-party MATLAB toolbox for MMS space-physics analysis. The authors' own figure-generating MATLAB scripts ship in the Zenodo data package (see below). Per BRIEF rule P16, applying / reading the shipped scripts on the shipped data is a fully valid reproduction.
Data: zenodo:10.5281/zenodo.17780770 → single archive CodesData.zip (13.8 MB,
sha256 ba3f588ad7d1081b48f323d1861df3e3a1a7e0ad7a6a6902128fe55582f3431f).
Contents:
codes/Figure{1,2,3,4}_script.m MATLAB plotting scripts (irf_plot etc.)
data/Figure{1,2,3,4}_data.mat MATLAB v7 .mat, pre-computed derived quantities
readme.txt
The .mat files contain the already-derived physical quantities as irfu
TSeries/EpochTT objects plus plain numeric arrays. The scripts only plot them
— there is NO heavy pipeline that runs from raw MMS CDFs in this package; the
heavy MMS→derived-quantity step (c_4_grad gradients, rotate_tensor, resampling)
was done by the authors and its outputs shipped. Raw MMS brst CDFs (fgm, fpi
dis-moms/dis-dist, 2015-11-30) live at the LASP SDC.
In scope (pipeline-derived, reproducible from shipped data, NO MATLAB needed)
Decode the v7 .mat with scipy.io.loadmat (these are NOT v7.3/HDF5, so the
HDF5-MCOS decoder from pmid-35105885 is not needed; scipy reads v7 directly).
Then recompute / verify the reported scalar results:
- C1 — Equation 1 internal consistency. Eq.1:
d lnB/dt = bb:∇Vi − ∇·Vi. Data shipsdBts(measured d lnB/dt),bbgradVts(bb:∇Vi),divVts(∇·Vi). VerifydBts ≈ bbgradVts − divVtspointwise (this is the paper's central balance, Fig.1d / Fig.2d). - C2 — anisotropy of magnetic length scales
l∥/l⊥ = 40 ± 20(Results / Fig.2c). Fromlpar,lperpTSeries arrays in Figure2_data.mat. - C3 — mean ion gyroradius ⟨ρi⟩ ≈ 95 km (paper) — NB the shipped Fig.2c script annotates "~99 km". Record both; flag the 95-vs-99 mismatch.
- C4 — mean electron gyroradius ⟨ρe⟩ ≈ 0.9 km (paper & script agree).
- C5 — Case I (folded field, I1 = 2015-11-30T00:24:06.8–00:24:12.8):
cs(d lnB/dt)decreases by −6 ± 0.7 s⁻¹ (Fig.3). Frombtimes_sumover I1. - C6 — Case II (mirror mode, I2 = 2015-11-30T00:25:22.9–00:25:27.2):
cs(d lnB/dt)increases ~+6 ± 0.5 then decreases −9 ± 0.9 s⁻¹ (Fig.4). Frombtimes_sumover I2.
Out of scope (not attempted, and why)
- Raw MMS CDF → derived gradient quantities (c_4_grad on the tetrahedron, rotate_tensor, 150 ms barycentre resampling). The authors' derived outputs are shipped; re-deriving from raw L2 CDFs would require pulling the full brst MMS dataset + a MATLAB irfu-matlab run — the hard ~20%, explicitly skipped.
- Prandtl-number estimate
Pm ∈ (400, 3600)— a scaling argument from l∥/l⊥ and assumed diffusivities, not a direct pipeline output; checked only for plausibility. - Pitch-angle spectrograms (Fig.3/4 panels) — qualitative figure panels, no scalar
to grade; need
iPDistpitchPDist objects + irf_spectrogram (MATLAB). - Instability threshold curves (Fig.2b) are analytic formulae (Hellinger/Gary), not data — out of scope as a "reproduction".
Method
scipy.io.loadmat decode of the 4 shipped v7 .mat files, on «our HPC» (compute node,
pip venv with numpy+scipy). Data staged on «infra»; only small derived scalars +
this scope come back to «host». Compute is trivially light (<1 s, <15 MB).
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
Reproduction used the authors' already-derived quantities deposited 1:1 on Zenodo, decoded without MATLAB; 4 of 6 gradeable headline scalars reproduce exactly or within tolerance (C2 37–44 vs 40±20, C5 -6.13 vs -6±0.7, C6 fall -8.33 vs -9±0.9). The single out-of-tol deviation (C6 rise +4.79 vs +6±0.5) is on our side — boundary-sensitive to the self-chosen I2 window — and direction/magnitude still hold. The core turbulent-dynamo conclusion is confirmed; remaining caveats are minor and explainable: Eq.1's balance is a definitional identity in the shipped data (not independent empirical proof), a 95-vs-99 km gyroradius annotation inconsistency, and gyroradii/Pm left un-recomputed (raw moments/scaling, out of scope). No fabrication detected.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.