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REVIEW 3 major objections 5 minor 69 references

The VVV near-IR galaxy catalogue of the southern Galactic disc

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read This paper presents a catalogue of 167,559 galaxies behind the southern Milky Way disc, found in near-infrared images with machine-learning classifiers and reaching $K_s^0 = 16$ mag with about 10% contamination and 78% completeness.

desk verdict A genuinely useful deep NIR galaxy catalogue for the ZoA with an honest, if unavoidable, circularity in its ML validation — worth refereeing and worth citing. read the letter →

arxiv 2506.19231 v1 pith:WCUO42EM submitted 2025-06-24 astro-ph.GA

M. V. Alonso , L. D. Baravalle , J. L. Nilo Castellón , C. Villalon , M. Soto , M. A. Sgró , I. V. Daza Perilla , C. Valotto
show 11 more authors
M. Lares D. Minniti P. Marchant Cortés F. Milla Castro M. Hempel J. Alonso-García L. Macri A. Pichel N. Masetti R. K. Saito M. Gómez
This is my paper · ORCID
classification astro-ph.GA
keywords ZoneofAvoidancenear-infraredgalaxycatalogueGalacticdiscVVVXsurveymachine-learningclassificationphotometrymorphologylarge-scalestructure
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

The paper sets out to close one of the last gaps in the nearby galaxy map: the Zone of Avoidance, the strip of sky hidden by the Milky Way's dust and stars. It presents a catalogue of 167,559 galaxies in the southern Galactic disc ($230^\circ < l < 350^\circ$, $|b| \le 4.5^\circ$), combining near-infrared images that penetrate dust with machine-learning classification to separate galaxies from stars and artifacts. Each entry carries positions, extinction-corrected $JHK_s$ magnitudes, morphological parameters, and two independent galaxy probabilities. The authors argue that the catalogue reaches $K_s^0 = 16$ mag with a contamination rate of about 10% and completeness of 78%, roughly two magnitudes deeper than the previous all-sky near-infrared extended-source catalogue over this region. If that holds, it is one of the deepest systematic maps yet of the obscured southern Galactic disc, and a foundation for redshift and large-scale-structure work.

What carries the argument

The central object is the catalogue itself, VVV NIRGC III, produced by a pipeline whose two working parts are source measurement and machine-learning classification. Extended sources are found with a source-extraction package and selected by half-light radius, concentration, stellar-likelihood index, and near-infrared colours that exclude most Galactic stars. Each surviving candidate is then scored twice: a convolutional neural network reads 44x44-pixel image stamps in $J$, $H$, and $K_s$, plus edge-filtered versions, while a gradient-boosting model uses 58 photometric and morphological features. The acceptance rule combines the two probabilities, and the claimed contamination and completeness numbers come from test-set metrics, an injection test with synthetic galaxies having a range of sizes and brightnesses, and visual inspection of subsets.

What would settle it

Run the synthetic injection test through the full pipeline instead of stopping at source extraction: inject synthetic galaxies with known $K_s$ magnitudes into VVVX tiles, pass them through the same colour cuts and both machine-learning classifiers, and compare the final recovered fraction with 78%. Alternatively, visually classify a random sample of roughly a thousand catalogue entries in deeper, higher-resolution images and count how many are genuine galaxies. A recovered fraction well below 78%, or a genuine fraction far below 90%, would falsify the catalogue's quoted performance.

Watch

Extended reading notes

Core claim

The central claim is that a two-step procedure can systematically uncover galaxies where the Milky Way's disc blocks the view. First, morphological and colour cuts isolate 692,694 extended extragalactic candidates from millions of detections in the VVVX near-infrared survey. Second, two independent machine-learning classifiers, an image-based convolutional neural network and a photometric gradient-boosting model, score each candidate, and 167,559 sources whose joint probabilities meet thresholds chosen to favour purity are kept. The test-set performance is 91% precision and 78% recall, and a separate visual check of sources left out of training gives 12% contamination and 80% completeness; about 14% of the final catalogue is visually confirmed or matched to earlier catalogues. The resulting map shows that apparent galaxy density across these 1080 square degrees is dominated by Milky Way extinction, with residual overdensities that may mark groups, clusters, and filaments. The paper presents this as the final catalogue of a series, bringing the total to 173,113 galaxies in this part of the Zone of Avoidance.

Load-bearing premise

The load-bearing premise is that the human visual labels used to train the machine-learning classifiers are unbiased in these crowded, dusty fields, since the classification step was never checked against an independent, deeper dataset; if those labels are systematically wrong, both the 10% contamination and 78% completeness figures would shift.

Editorial extensions

If this is right

  • Astronomers get a public catalogue of 167,559 galaxies with positions, magnitudes, colours, morphology, and machine-learning probabilities across 1080 square degrees of the southern Galactic disc.
  • The catalogue reaches roughly two magnitudes deeper than the earlier all-sky near-infrared extended-source catalogue, so large-scale structures behind the Milky Way can be traced closer to the Galactic plane.
  • Its 14% confirmed subsample anchors the rest: 6,058 matches to earlier near-infrared galaxies, 493 spectroscopic redshifts with a median near 0.02, and 3,670 photometric redshifts with a median near 0.06.
  • Candidate overdensities in the Norma and Vela regions give radio and optical follow-up programmes specific targets, and the catalogue is positioned as a bridge to forthcoming surveys of the Zone of Avoidance.
  • The full 692,694-entry candidate list, without probability cuts, is available on request, which lets other groups retune the selection to their own purity requirements.

Reading between the lines

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

  • Editorial extension: the completeness test in the paper stops at source detection, so the quoted 78% completeness could be retested by injecting synthetic galaxies through the full convolutional-neural-network and gradient-boosting classification chain, not just the extraction step.
  • Editorial extension: because the catalogue is selected in near-infrared light, it is probably biased toward early-type and massive galaxies; pairing it with radio HI galaxy samples, which favour gas-rich late types, would likely recover a more complete census of the Zone of Avoidance than either band alone.
  • Editorial extension: the small visually confirmed subsample, about 14%, may not represent the faintest or most crowded entries, so users studying galaxy density should check whether inferred structures change when the catalogue is restricted to visually confirmed or large half-light-radius sources.
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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

3 major / 5 minor

Summary. Alonso et al. present VVV NIRGC III, a near-infrared catalogue of 167,559 galaxy candidates in the southern Galactic disc (230deg <= l <= 350deg, |b| <= 4.5deg), built from VVVX JHK_s images. Sources are extracted with SExtractor+PSFEx, selected using morphological and colour criteria, and classified with two machine-learning algorithms: a CNN applied to image stamps and XGBoost applied to photometric/morphological features. The catalogue provides positions, extinction-corrected photometry, morphology, galaxy probabilities, and flags; 14% of the entries are said to be confirmed by visual inspection or external catalogues. The authors claim a contamination rate of about 10% and a completeness of 78% at the adopted probability thresholds, reaching Ks ~ 16 mag, and use the catalogue to map galaxy density across the Zone of Avoidance.

Significance. If the classification quality is confirmed, this is a valuable contribution: it pushes NIR galaxy detection in the Zone of Avoidance more than 2 mag deeper than 2MASS over 1080 sq deg, provides a large public list of candidates with probabilities and photometry, and complements HI and radio surveys. The paper's strengths include explicit detection-completeness simulations from injected synthetic galaxies, internal magnitude comparisons in tile overlaps, photometric transformation to the 2MASS system, and extensive cross-matches with 2MASS, WISE, and redshift catalogues. However, the headline precision and recall figures are not yet independently anchored, so the quantitative claims about contamination and completeness need revision before the catalogue can be used at face value.

major comments (3)
  1. [§3.2, §3.3, §4] The values precision=0.91 and recall=0.78 quoted in §4 come from the test set constructed by the same visual-inspection process that produced the training labels used for the CNN and XGBoost classifiers in §3.3, while §3.2 explicitly states that the completeness characterization was limited to SExtractor+PSFEx detection and did not extend to classification. The catalogue-level claims of 'contamination rate due to misclassifications of less than 10%' and 'completeness of 78%' therefore rest on an unanchored validation step: if the visual labels are biased in crowded, dusty, low-latitude fields, the bias enters the training labels, the test metrics, and the post-classification visual check alike. The authors should either validate the classifiers against an independent ground truth (e.g., blind visual inspection of a stratified random sample, or galaxies confirmed by 2MASS, radio, or redshift data and not used in training) or explicitly relabel these numbers as test-set performance estimates in §4, the abstract, and §7, with the corresponding uncertainty attached to all catalogue-level statements.
  2. [§4] The post-classification visual check mentioned in §4 (12% contamination, 80% completeness) is not described as a stratified random sample, and the text notes that the 16,998 visually confirmed galaxies lie preferentially in regions of relatively mild interstellar extinction. Since the risk of misclassification is concentrated in the faint, small-R1/2 population (completeness drops to 61% for 0.6<R1/2<0.8 arcsec) and in high-extinction and high-density regions, this check cannot certify the 86% of catalogue entries that were not visually inspected. Please specify how the post-classification sample was selected, demonstrate its representativeness in Ks, R1/2, extinction, and stellar density, or remove the claim that the two metrics are 'in good agreement' with each other.
  3. [Abstract, §5, §7] The paper repeatedly states that the catalogue reaches Ks0=16 mag, quoting the 80% detection completeness from the §3.2 injection simulations, but the classification recall is 78% on the test set and is not part of those simulations. If detection and classification are treated as sequential and independent, the end-to-end completeness at the survey limit is approximately 0.62, not 0.78 or 0.80. Please state explicitly whether 'complete to Ks=16' refers to the SExtractor+PSFEx detection step only or to the final published catalogue, and either provide an end-to-end completeness measurement or avoid conflating the two numbers in the abstract and conclusions.
minor comments (5)
  1. [Table 2] The first ten catalogue rows all have Gx flag=1 and IS/PS probabilities set to 1.0 because they are drawn from the training or inspection sample; a random selection from the full catalogue with typical probability values would better illustrate the product.
  2. [§4.2.3] The discussion of 2MASS extended sources not matched (4,314) and redshift-known galaxies not included (43) is anecdotal; a quantitative comparison of their magnitude, colour, and size distributions would help users assess the selection bias.
  3. [§7] The 692,694-source candidate table is said to be available upon request; it should be deposited in full alongside the main catalogue so that users can apply their own probability thresholds and reproduce the analysis.
  4. [§6] Figure 10 relies on an unpublished stellar density map (Alonso-García et al., in prep.); since the extinction-density argument is central to the paper, the map needs a public source or a full description in the caption or appendix.
  5. [Throughout] There are minor copy-editing issues: 'NIRCG' appears for 'NIRGC' in §4.2.2; 'Sersic' should be 'Sérsic'; and the definition of the 23,333 'confirmed galaxies' in §7 should clarify how the 16,998 visually confirmed objects overlap with the 6,058 2MASS matches and the redshift matches before claiming to be 'without duplicates'.

Circularity Check

1 steps flagged · score 2.0 of 10

Minor fitted-input-called-prediction issue: the catalogue's quoted 10% contamination and 78% completeness are the precision and recall of the same test set used to choose the probability thresholds, and the paper explicitly stops short of an independent classification validation.

  1. fitted input called prediction [Section 4 (VVV NIRGC III catalogue definition) and Section 3.3 (Classification of possible extragalactic sources)]
    "These probability limits were determined through the analysis of the recall-precision curves in Figure 2 and a meticulous visual inspection of several sources... These joint probability limits yield a precision of 0.91 and a recall of 0.78 for the test set. These values indicate a contamination rate due to misclassifications of less than 10% in our final catalogue and a completeness of 78%."

    The thresholds defining the catalogue are selected using the recall-precision curves computed on the test set (Fig. 2, §3.3). The reported 'contamination rate' and 'completeness' are then exactly the precision and recall of that same test set at the selected thresholds, so the headline quality numbers are the values of the curve used for selection, not independent predictions. The later post-classification visual check (12% contamination, 80% completeness) uses a disjoint sample but the same visual-inspection labelling method that generated the training data, so it does not remove the dependence on that ground truth.

full rationale

The catalogue itself is an observed data product, not a derived quantity, and most of the pipeline (SExtractor+PSFEx detection, morphological and colour cuts, photometric zero-point and extinction corrections, cross-matches with 2MASS, WISE, and redshift compilations) is externally checkable and not circular. The main circularity-relevant issue is concentrated in the quantitative purity/completeness claims: the probability thresholds are chosen by inspecting the test-set recall-precision curves, and the same test-set precision (0.91) and recall (0.78) are then quoted as the catalogue's 'less than 10% contamination' and '78% completeness.' This is a fitted-input-called-prediction pattern, though it is a mild one because the test set is disjoint from the training set and a post-classification visual check (12% contamination, 80% completeness) provides partial corroboration. The paper itself flags the key limitation in §3.2: detection completeness was characterized only up to the SExtractor+PSFEx step and 'did not extend it to the subsequent classification,' with a full evaluation requiring an independent, more sensitive dataset. That admission is a validation gap, not by itself a logical circle; however, it means the headline contamination/completeness numbers rest on the same visual ground truth used to train the classifiers. No self-citation is load-bearing: the prior methodology (Baravalle et al. 2018, 2021; Daza-Perilla et al. 2023) is described rather than invoked as an unverified uniqueness theorem, and the present paper applies and checks it on new data. The density maps and large-scale-structure discussion are not circular because they are interpretations of the new catalogue. Overall the derivation chain is mostly self-contained and externally grounded, with one minor circular step in the validation metrics, warranting a score of 2.

Assumptions & free parameters 4 free parameters · 7 assumptions · 0 invented entities

The catalogue rests on hand-chosen probability thresholds and colour/morphology cuts, plus the assumption that visual inspection is an unbiased ground truth. No new physical entities are introduced.

free parameters (4)
  • CNN/XGBoost probability thresholds = joint probability >=0.6, or 0.5<IS-CNN<0.6 and PS-XGBoost>=0.8
    Chosen from precision-recall analysis and visual inspection to prioritize purity over completeness; not externally calibrated.
  • NIR colour selection cuts = 0.6<(J-Ks)_0<2.0, 0.0<(J-H)_0<1.0, 0.0<(H-Ks)_0<2.0, (J-H)_0+0.9(H-Ks)_0>0.44
    Defined in Baravalle et al. (2021) using colour-magnitude diagrams and visual inspection; applied here to select extragalactic candidates.
  • Morphological selection criteria = PHI>0.002, 2.1<C<5, R1/2 and CLASS_STAR limits depending on Ks magnitude
    Adopted from the authors' previous work to separate extended sources from point sources; hand-tuned for this area.
  • SExtractor configuration parameters = not fully specified (modified minimum pixels, deblending, background estimation)
    The configuration was 'slightly modified' for the lower extinction and crowding of the southern disc, but the exact values are not given.
assumptions (7)
  • domain assumption Visual inspection of VVV/VVVX images provides a reliable ground-truth label for whether a source is a galaxy.
    Used throughout Section 3.3 and Section 4 to create training labels, set probability thresholds, and estimate contamination/completeness.
  • domain assumption The colour and morphological criteria inherited from Baravalle et al. (2018, 2021) separate galaxies from Galactic sources at these low latitudes.
    Section 3.3 applies these cuts before ML classification; the cuts were originally tuned on the inner disc and are assumed to transfer to the outer southern disc.
  • domain assumption Synthetic galaxies built from Sersic bulge+disc components with the adopted parameter ranges are representative of real galaxies in the survey.
    Section 3.2 uses these injections to estimate detection completeness; if the simulated population does not match reality, the completeness estimate is wrong.
  • domain assumption Models trained on northern-disc VVVX data plus 23 visually inspected southern tiles generalize to the full southern disc.
    Section 3.3 uses transfer learning; no independent validation set outside these tiles is used.
  • domain assumption The Schlafly and Finkbeiner (2011) extinction maps and Catelan et al. (2011) extinction coefficients correctly correct the NIR magnitudes.
    Section 4 uses these to deredden magnitudes and colors; errors here would bias photometry and colour cuts.
  • domain assumption The 2MASS photometric system transformation computed per tile is accurate.
    Section 4 uses it to put VVVX magnitudes on the 2MASS system for comparisons and catalogue use.
  • standard math Cosmological parameters H0=70.4 km/s/Mpc, OmegaM=0.272, OmegaLambda=0.728 are assumed.
    Stated in the introduction, though not used in any derived distances in this work.

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Cite this review

Pith. "Pith review of The VVV near-IR galaxy catalogue of the southern Galactic disc." pith.science (2026). https://pith.science/paper/WCUO42EM

@misc{pith2026250619231,
  author       = {Pith},
  title        = {Pith review of: The VVV near-IR galaxy catalogue of the southern Galactic disc},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/WCUO42EM}},
  note         = {Machine review of arXiv:2506.19231}
}
abstract

The distribution of galaxies in the Zone of Avoidance (ZoA) is incomplete due to the presence of our own Galaxy. Our research focused on the identification and characterisation of galaxies in the ZoA, using the new near-infrared data from the VVVX survey in the regions that cover the southern Galactic disc. We used our previously-established procedure based on photometric and morphological criteria to identify galaxies. The large data volume collected by the VVVX required alternatives to visual inspection, including artificial intelligence techniques, such as classifiers based on neural networks. The VVV NIR galaxy catalogue is presented, covering the southern Galactic disc, significantly extending the vision down to $K^0_s=16$ mag throughout the ZoA. This catalogue provides positions, photometric and morphological parameters for a total of 167,559 galaxies with their probabilities determined by the CNN and XGBoost algorithms based on image and photometric data, respectively. The construction of the catalogue involves the employment of optimal probability criteria. 14% of these galaxies were confirmed by visual inspection or by matching with previous catalogues. The peculiarities exhibited by distinct regions across the Galactic disc, along with the characteristics of the galaxies, are thoroughly examined. The catalogue serves as a valuable resource for extragalactic studies within the ZoA, providing a crucial complement to the forthcoming radio catalogues and future surveys utilizing the Vera C.~Rubin Observatory and the Nancy Grace Roman Space Telescope. We present a deep galaxy map, covering a 1080 sq. deg. region, which reveals that the apparent galaxy density is predominantly influenced by foreground extinction from the Milky Way. However, the presence of intrinsic inhomogeneities, potentially associated with candidate galaxy groups or clusters and filaments, is also discernible.

Figures

Figures reproduced from arXiv: 2506.19231 by the authors.

Figure 1
Figure 1. Completeness in percentage for input Ks magnitudes of synthetic galaxy detections. The grey and black dots, along with the solid line, correspond to the results of the e1114 and e0605 tiles, respectively. The 80% completeness level is also shown. and the parameters used by our adopted machine-learning tech￾niques lies beyond the scope of this work. 3.3. Classification of possible extragalactic sources To distinguish… view at source ↗
Figure 2
Figure 2. Recall-Precision curves for the IS-CNN and PS-XGBoost mod￾els. The red crosses indicate the most common threshold value of 0.5. Other threshold values are indicated by the colour bar. results will be high. For this work, we prioritize a better preci￾sion than recall in order to emphasize purity over completeness. 4. The VVV near-IR galaxy catalogue III We applied the improved procedure and obtained 692,694 possi￾ble… view at source ↗
Figure 3
Figure 3. Examples of false detections. From left to right panels, two Galactic star forming regions and a spike are shown in the central parts of the VVVX images. North is up and east is to the left. able spectroscopic and photometric redshifts, respectively. This catalogue is available in electronic format 4 . The complete cata￾logue of 692,694 possible extragalactic sources, along with their probabilities of being galaxies… view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: shows the distribution of the interstellar extinc￾tions in the Ks passband for the VVV NIRGC catalogues, in bin counts normalized with the total sample size (N). It is evi￾dent from this figure that the regions of VVV NIRGC I, or the inner parts of the southern Galacti…
Figure 5
Figure 5. Figure 5: Internal magnitude comparisons in the three NIR passbands of the VVVX survey. The colour bar indicates the probability density function (PDF) estimated using a Gaussian kernel density estimation. (WISE, Wright et al. 2010), producing 90,123 galaxies in com￾mon. The WIS…
Figure 6
Figure 6. Figure 6: The comparison between the total magnitudes of VVV NIRGC III and the 2MASX in the three NIR passbands. The colour bar indicates the PDF estimated using a Gaussian kernel density estimation, as shown in Fig.5 with the works of Rajohnson et al. (2024a,b) using an angular…
Figure 7
Figure 7. Figure 7: Distributions of the photometric parameters K 0 s magnitudes and colours (J − Ks) 0 and (H − Ks) 0 [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]
Figure 8
Figure 8. Figure 8: Distributions of the morphological parameters: half-light radius, concentration index and Sersic index. The y-axis of the first distribution is in logarithmic scale [PITH_FULL_IMAGE:figures/full_fig_p010_8.png]
Figure 9
Figure 9. Figure 9: Examples of the largest galaxies found in VVV NIRGC III. Upper panels show spiral galaxies and bottom panels, early-types. North is up and east is to the left. quest, it is available the larger catalogue of all NIR extragalactic candidate sources, with a total of 692,6…
Figure 10
Figure 10. Figure 10: Distribution of the galaxies in the southern Galactic disc using the VVV and VVVX surveys superimposed with the stellar density map with limiting magnitude of Ks = 16 mag by Alonso-García et al. (in prep.). The colour bar shows, on linear scale, the variation of the s…

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