Pith. sign in

REVIEW 3 major objections 5 minor 104 references

Analysis of the Internal Radial Gradient of Chemical Abundances in Spiral Galaxies from CALIFA

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read The inner drop in spiral-galaxy oxygen gradients is real but rare: after diffuse-gas subtraction and a six-criterion consistency test, it appears only in galaxies with stellar mass above 10.2 solar masses, and its position and slope track…

desk verdict A careful CALIFA re-analysis of inner drops in abundance gradients, whose headline mass-exclusivity claim rests on an arbitrary and non-independent 'three of six criteria' rule. read the letter →

arxiv 2411.15327 v1 pith:XIE3XILJ submitted 2024-11-22 astro-ph.GA

A. F. S. Cardoso , O. Cavichia , M. Mollá , L. Sánchez-Menguiano This is my paper · ORCID
classification astro-ph.GA
keywords oxygenabundancegradientsinnerdropHIIregionselectiondiffuseionizedgasspiralgalaxiesgalacticbulgeschemicalevolutionintegralfieldspectroscopy
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

Spiral disks are expected to show oxygen abundances that decline smoothly outward, but some massive galaxies show an inner drop, a break near the center where the gradient flattens or inverts before settling onto the steeper outer gradient. The paper asks whether these drops are genuine features of galaxy chemistry or artifacts of how H II regions are selected, and it treats the question as a measurement problem: 147 spiral galaxies, six published selection criteria, and samples with and without subtraction of diffuse ionized gas. It finds that whether a drop appears can change with both choices, so only drops confirmed by at least three criteria after gas subtraction are counted; that leaves 15 galaxies, every one with $\log(M_*/M_\odot) > 10.2$. In those galaxies the drop sits on average near $0.84\,r_e$, the main oxygen gradient is steeper than in galaxies without a drop, and the drop position and inner slope correlate with galaxy and bulge mass. If this is right, the inner drop is a rare phenomenon tied to massive systems and their bulges rather than a universal feature of spiral disks, and earlier single-criterion reports need revisiting.

What carries the argument

The load-bearing machinery is a piecewise-linear fit to each galaxy's radial abundance profile, computed by an iterative breakpoint-regression algorithm and selected among one-segment, one-break, and two-break models by the corrected Akaike Information Criterion, with 2,000 bootstrap resamples to avoid local minima. An inner drop is declared when a break in the inner part of the radial distribution has an inner slope $a_1$ less negative than the main slope $a_2$. Six H II region selection criteria are applied: three BPT diagram demarcations (line-ratio curves separating star-forming regions from active galactic nuclei), the WHAN diagram classification (based on [N II]/H$\alpha$ and H$\alpha$ equivalent width), a young-stellar-luminosity fraction, and the BPT with an equivalent-width cut; a separate pipeline subtracts diffuse ionized gas before the same fits. The operational definition of a genuine inner drop is detection in at least three of the six criteria after DIG subtraction, which selects the 15-galaxy sample used for all physical correlations.

What would settle it

Apply the same six-criterion, diffuse-gas-subtracted pipeline to low-mass spiral galaxies, those with stellar mass below $\log(M_*/M_\odot) = 10.2$, that have enough H II regions in their inner regions; if any one shows an inner drop in at least three criteria, the claimed mass exclusivity is falsified. Alternatively, replace the three-of-six rule with a continuous detection score and check whether the 10.2 boundary and the mass correlations survive.

Watch

Extended reading notes

Core claim

The central claim is that the inner drop in the oxygen abundance radial gradient is a selection-dependent observable whose genuine occurrence is confined to massive spiral galaxies. Applying the six H II region criteria to the DIG-contaminated sample yields 13 to 24 galaxies with an inner drop depending on the criterion, and DIG decontamination changes which galaxies show the drop in both directions; for example, one galaxy loses its drop and another gains one after subtraction. After requiring detection in at least three of the six criteria in the DIG-subtracted sample, 15 galaxies remain, and all have $\log(M_*/M_\odot) > 10.2$. For these 15, the mean break position is $\langle h_1\rangle = 0.84 \pm 0.26\,r_e$, the mean main slope is $\langle a_2\rangle = -0.19 \pm 0.09$ dex/$r_e$, steeper than the $-0.08 \pm 0.09$ dex/$r_e$ common gradient, and the drop position anticorrelates with galaxy and bulge mass while the inner slope correlates with both. The paper interprets this as evidence that the inner drop marks the bulge-disk interface in massive galaxies, consistent with inside-out bulge formation, rather than a property of all spiral disks.

Load-bearing premise

The load-bearing premise is that a genuine inner drop is one detected in at least three of the six H II region selection criteria after diffuse-gas subtraction; that threshold is chosen after the fact, and a different threshold or a continuous score would change which 15 galaxies are analyzed and likely the correlations that follow.

Editorial extensions

If this is right

  • Inner-drop galaxies have a steeper main oxygen gradient ($\langle a_2\rangle = -0.19 \pm 0.09$ dex/$r_e$) than the canonical $-0.08$ dex/$r_e$, so the inner break and the steepened disk gradient appear to be one linked phenomenon.
  • The mass exclusivity result means chemical evolution models must explain why no spiral below $\log(M_*/M_\odot) = 10.2$ in this sample shows a drop, not just why some massive galaxies do.
  • Because the drop position and inner slope correlate with galaxy mass and bulge mass, more massive galaxies and more massive bulges are expected to show drops closer to the center and steeper inner gradients.
  • Earlier inner-drop detections based on a single H II region criterion or without diffuse-gas subtraction can be artifacts: the criterion used changes both the number of galaxies with drops and the position and slope of the drop.
  • The typical drop position near $0.8$-$0.9\,r_e$ places the break near the bulge-disk interface, connecting the observed feature to the formation timescale difference between bulge and disk.

Reading between the lines

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

  • The three-of-six threshold is arbitrary; replacing it with a continuous score (fraction of criteria detecting a drop, weighted by fit uncertainties) would likely shift which galaxies count and could soften or sharpen the $\log(M_*/M_\odot) = 10.2$ boundary. This is a testable reframing, not a paper claim.
  • The same pipeline applied to other integral-field spectroscopic samples with different spatial resolution and DIG properties would test whether the mass threshold and the bulge correlations are universal or specific to the present sample.
  • If the drop marks the bulge-disk interface, then classical bulges and pseudobulges should show systematically different drop depths or positions; the paper's bulge-mass correlations motivate that comparison even though the paper does not make it.
  • A direct prediction for high-resolution follow-up: low-mass spirals ($\log(M_*/M_\odot) < 10.2$) should show smooth single-slope abundance profiles in their inner regions, and massive spirals should show the drop only when the bulge is sufficiently massive.
Share X Bluesky LinkedIn Reddit HN

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. This paper analyzes the inner radial gradient of oxygen abundances in a sample of 147 spiral galaxies from CALIFA DR3 using H II region catalogs from Espinosa-Ponce et al. (2020). Six H II region selection criteria are compared (KE01, KA03, ST06, CF11, SA14, KE6A), with and without diffuse ionized gas (DIG) decontamination. Abundance gradients are fitted with piecewise linear models (single, one breakpoint, two breakpoints) using a bootstrap procedure and AICc model selection. The authors find that the presence and shape of inner drops depend strongly on the H II region selection criterion and on DIG decontamination; after DIG decontamination, 32 galaxies show an inner drop in at least one criterion, and 15 galaxies show one in at least three criteria. All 15 have log(M*/M_sun) > 10.2, leading to the claim that inner drops are exclusive to massive galaxies. They also report correlations between the inner drop position h1 and slope a1 with galaxy mass, bulge mass, and bulge effective radius.

Significance. If the mass-exclusivity result is correct, it would sharpen the picture of inner abundance drops as rare features tied to massive galaxies with bulges, with implications for inside-out formation and radial gas flows. The paper's strengths are its use of public CALIFA data and published catalogs, the explicit comparison of six selection criteria and DIG decontamination, and the automated, reproducible fitting methodology with bootstrap and AICc. However, the central claims rest on a small, threshold-defined subsample (15 galaxies, 13 with bulge parameters), and the robustness rule ('at least three of six criteria') is not shown to be a valid reliability filter. The correlations in Fig. 11 are based on ~13-15 points with modest coefficients and no significance estimates. These issues must be addressed before the conclusions can be fully accepted.

major comments (3)
  1. The definition of a 'genuine' inner drop as one detected in at least three of the six H II region selection criteria after DIG decontamination is an ad hoc threshold. The six criteria are not independent: KE01 and KE6A are the same BPT demarcation with a minor EW(Halpha)>6 A filter and often produce identical detections; KA03 and ST06 are overlapping BPT variants; CF11 and SA14 are both related to EW/luminosity cuts. Consequently, 'three of six' may effectively be only one or two independent detections, and the threshold acts as a hidden filter that preferentially removes lower-mass galaxies with sparser inner-disk sampling (e.g., NGC 2805 with log M*/M_sun about 10.1 and NGC 5205 about 9.9). The paper does not show that these excluded galaxies have comparable sampling and would have been detected under a less restrictive rule. The claim 'we only identified inner drops in galaxies with log(M*/M_sun) > 10.2' and the Fig. 11 correlations are therefore conditional on an arbitrary, non-independent majority rule. A quantitative robustness analysis (e.g., varying the threshold from 1 to 6, or using a continuous detection score, and checking the inner-disk H II region sampling of the excluded galaxies) is needed to support the mass-exclusivity claim.
  2. [Section 4.2, Figure 11] The weighted Pearson correlation coefficients are reported for samples of only 15 galaxies (13 for bulge parameters) without p-values, confidence intervals, or a demonstration that the weighted fit is appropriate. Coefficients are modest (r = -0.53, -0.50, -0.47 for h1; r = 0.55, 0.27, -0.04 for a1), and given the large error bars and small N, the claims of correlations with galaxy mass and bulge mass should be quantified with a significance test and ideally a bootstrap confidence interval. In particular, the r = 0.27 and r = -0.04 values in panels (e) and (f) do not support the text's statement that there are correlations with bulge mass and no correlation with bulge effective radius; the authors should either report formal significance or soften the claims.
  3. [Section 3.2 and Table 5] The average h1 for the 15 galaxies is obtained by averaging only the criteria in which an inner drop was detected, weighted by the fitting errors. This averaging procedure is biased because the detection of an inner drop is itself dependent on the number and radial distribution of H II regions in the inner disk; criteria that fail to detect a drop are excluded, so the mean h1 and a1 are not representative of the galaxy's underlying gradient. The paper should provide a sensitivity test showing how the averaged coefficients change when the undetected criteria are included (e.g., as upper/lower limits) or when the analysis is restricted to criteria that always detect the drop.
minor comments (5)
  1. [Abstract] The phrase 'galaxies evolution' should be 'galaxy evolution', and 'over the featuring inner drops' in the abstract is awkward; consider rewording for clarity.
  2. [Section 2.1.4] There is a typo: 'hefereafter SA14' should be 'hereafter SA14'.
  3. [Table 3] The '% inner drop' columns are not clearly explained as the frequency per galaxy over the six criteria, and the empty cells ('–') could be confused with non-detection; consider adding a footnote defining '–' separately for the C and D entries.
  4. [Section 5] The paper acknowledges that 'these are still preliminary results and detailed CEM for spiral galaxies with different masses will be published in a forthcoming work,' which is appropriate, but the discussion does not revisit the limitations of the 15-galaxy sample when interpreting the model comparison in Fig. 12.
  5. [Section 2.1.1] The term 'hDIG' is defined as regions with EW(Halpha) < 3 A, but the notation is not standard; consider a glossary or explicit definition at first use to avoid confusion with mDIG and SFc.

Circularity Check

0 steps flagged · score 2.0 of 10

No circular derivation; the central analysis is an empirical, external-data study. The 'three-of-six criteria' sample rule conditions the mass-exclusivity claim, but it does not reduce the conclusion to its own inputs by construction.

full rationale

The paper's central results are derived from external data products (CALIFA DR3, the Espinosa-Ponce et al. 2020 H II region catalog, the Mendez-Abreu et al. 2017 bulge catalog) and literature calibrations (Pettini & Pagel 2004 O3N2). The automated piecewise-regression fitting with bootstrap and AIC model selection is an independent measurement procedure, not a quantity fitted to the conclusions. The 'inner drop in at least three criteria after DIG decontamination' rule (Section 4.2) is a sample-selection threshold; the claim 'we only identified inner drops in galaxies with log(M*/M_sun) > 10.2' is logically conditional on that threshold, and lower-mass galaxies with drops in one or two criteria are excluded from the 'robust' sample (e.g., NGC 2805 and NGC 5205 in Table 3). This is a selection-effect robustness concern, not circularity, because the threshold is not defined in terms of stellar mass and the paper does not fit a parameter to a subset and then rename it a prediction. Self-citations to SM16, SM18, and Cavichia et al. 2023 are used for comparison, context, and a preliminary model comparison; the new correlations in Figure 11 are computed from the present fits and do not reduce to those papers. No load-bearing argument relies on an unverified self-citation. Score 2 reflects only the presence of minor, non-load-bearing self-citations.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The central empirical claims rest on literature catalogs, calibration choices, and an ad hoc robustness threshold. No new physical entities, forces, or dimensions are introduced.

free parameters (3)
  • inner drop position h1 (per galaxy) = mean 0.84 +/- 0.26 r_e, range 0.45 to 1.35 r_e
    Fitted breakpoint from piecewise regression (Eqs. 5 and 6); it is the dependent variable in the correlations with galaxy mass, bulge mass, and bulge effective radius (Fig. 11).
  • inner gradient slope a1 (per galaxy) = mean 0.12 +/- 0.11 dex/re
    Fitted slope of the internal radial gradient; used as the dependent variable in the correlations with galaxy and bulge mass.
  • main gradient slope a2 (per galaxy) = mean -0.19 +/- 0.09 dex/re for galaxies with inner drop
    Fitted slope of the main gradient; used to compare galaxies with and without inner drops and to compare with previous SM16 and SM18 values.
assumptions (4)
  • domain assumption Oxygen abundances are derived from the O3N2 index using the Pettini and Pagel (2004) calibration.
    All gradient fits and inner drop classifications use 12+log(O/H) from the O3N2 PP04 calibration. The paper shows that using a different calibrator changes the number of detected inner drops (Section 4.1), so this choice is load-bearing but taken from the literature.
  • ad hoc to paper A galaxy is classified as having a genuine inner drop only if detected in at least three of the six H II region selection criteria after DIG decontamination.
    Section 4.2 selects the 15 galaxies that consistently show an inner drop in at least three criteria. This threshold is not derived from an external benchmark and directly controls the sample used for all subsequent correlations.
  • domain assumption Gradient model selection assumes Gaussian residuals in the AIC log-likelihood (Eq. 8) and that up to two breakpoints capture the radial profile.
    The fit quality and breakpoint confidence intervals depend on these statistical assumptions. No alternative model family, such as curved or nonparametric profiles, is tested.
  • domain assumption Bulge masses are computed via Eq. 1 using the Sani et al. (2011) relation for velocity dispersion and the Prugniel and Simien (1997) alpha relation.
    Two of the 15 inner drop galaxies lack bulge parameters, and the bulge mass correlations rely on these literature scaling relations rather than on direct measurements.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Analysis of the Internal Radial Gradient of Chemical Abundances in Spiral Galaxies from CALIFA." pith.science (2026). https://pith.science/paper/XIE3XILJ

@misc{pith2026241115327,
  author       = {Pith},
  title        = {Pith review of: Analysis of the Internal Radial Gradient of Chemical Abundances in Spiral Galaxies from CALIFA},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XIE3XILJ}},
  note         = {Machine review of arXiv:2411.15327}
}
read the original abstract

The study of chemical evolution is of paramount importance for understanding the galaxies evolution. Models and observations propose an inside-out mechanism in the formation of spiral galaxy disks implying a negative radial gradient of elemental abundances when represented in logarithmic scale. However, observed chemical abundance gradients, in some instances, deviate from a single linear negative straight line, revealing inner drops or outer flattenings, particularly in more massive galaxies. This study analyzes oxygen abundance gradients in spiral galaxies based on observations from the Calar Alto Legacy Integral Field Area (CALIFA) survey. Our focus is specifically on examining oxygen abundance gradient profiles, as obtained with data from HII regions, with a special emphasis on the inner radial gradient. We employ an automated fitting procedure to establish correlations between the physical properties of galaxies and bulges and the presence of these inner drops, seeking for potential explanations for these gradient variations. We find that the different criteria used in the literature to distinguish HII regions from other ionization sources in the galaxy, such as Active Galactic Nuclei, significantly impact the results, potentially altering abundance gradient profiles and uncovering galaxies with distinct inner drops. Additionally, we analyze the abundance radial gradients to investigate the impact of diffuse ionized gas (DIG) decontamination on oxygen abundances over the featuring inner drops. We observe that DIG, concentrated mainly in the central regions of galaxies, can modify oxygen abundance gradient profiles if left unaddressed.

Figures

Figures reproduced from arXiv: 2411.15327 by the authors.

Figure 1
Figure 1. Distribution of properties of galaxies in our sample according to log(M∗/M⊙), morphological type, and effective radii re, shown in the left, central, and right panels, respectively. The morphological classification in the central panels, from “a” to “dm”, corresponds to spiral galaxies in the Hubble diagram classified as early-type to late-type galaxies, respectively. The top panels show the distribution of the samp… view at source ↗
Figure 2
Figure 2. Radial distribution of ionized regions in galaxies, separated into hDIG, mDIG, SFc, as shown in the top, mid￾dle, and bottom panels, respectively, indicates the number of ionized regions for each classification. The boxplots pro￾vide the median of each classification, as well as the points considered outliers. (Walcher et al. 2014), and considering that Hii regions have sizes on the order of a hundred to several hun… view at source ↗
Figure 3
Figure 3. The BPT diagrams of the data samples indicate demarcation curves in the separation between Hii regions and AGNs as follows: dashed line: KE01; dash-dotted line: ST06; dotted line: KA03, as shown in the legend. The top panels, identified as with DIG contamination, correspond to the sample of 11,410 ionized regions. The middle panels, identified as without DIG contamination, correspond to the sample of 10,974 ionized … view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: The WHAN diagram from CF11 classifying the ionized regions of the samples with and without DIG con￾tamination is shown in the upper and lower panels, respec￾tively, as indicated in each panel. The percentage of regions classified as SF (star-forming), wAGN (weak AGN), …
Figure 5
Figure 5. Figure 5: Example of a fit performed using the piecewise regression from Pilgrim (2021), illustrating the free param￾eters of the fit expressed in Equations 4, 5 and 6. The blue dots represent the selected Hii regions according to the Kauffmann et al. (2003) criterion, with corr…
Figure 6
Figure 6. Figure 6: Profiles of abundance gradients without DIG contamination. In each panel in the graphs, the blue points correspond to the Hii regions selected by each criterion. The colored solid curve corresponds to the fit of that specific criterion, indicated in the upper right cor…
Figure 8
Figure 8. Figure 8: Diagrams depicting the number of galaxies with an inner drop using different Hii region selection methods, with and without DIG contamination, differentiated by red and blue colors as indicated in the legend. At the center of each panel is the intersection indicating t…
Figure 7
Figure 7. Figure 7: Profiles of oxygen gradients of four galaxies from the sample with and without DIG contamination, rep￾resented by red stars and blue squares, respectively. The Hii regions were selected according to SA14 criterion. The solid red and dashed blue lines correspond to the …
Figure 9
Figure 9. Figure 9: Distribution of the number of galaxies that ex￾hibit an inner drop (in blue) compared to galaxies without an inner drop (in red), considering the 15 galaxies that showed an inner drop in at least three Hii region selection criteria, as shown in [PITH_FULL_IMAGE:figure…
Figure 10
Figure 10. Figure 10: Relation of the coefficients of the fit with the presence or absence of the bar for the 15 galaxies that ex￾hibited an inner drop in at least three methods of selection of Hii regions, as shown in [PITH_FULL_IMAGE:figures/full_fig_p017_10.png]
Figure 11
Figure 11. Figure 11: Relationships between the mean position where the inner drop occurs (h1) with the galaxy and bulge masses and and the bulge effective radius presented in panels a) to c). Panels d) to f) show the same relations but for the slope of the inner radial abundance gradient …
Figure 12
Figure 12. Figure 12: Oxygen abundance radial profile for NGC 4047 (blue filled circles) obtained using KA03 H II region selec￾tion method. The dashed vertical line marks the position 0.64 r/re where an inner drop is detected for this galaxy. The red continuous line corresponds to prelimin…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

104 extracted references · 13 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    Estimating regression models with unknown break-points

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

    arXiv 2021

  4. [4]

    1973, Akad \'e miai Kiad \'o , Budapest

    Akaike, H. 1973, Akad \'e miai Kiad \'o , Budapest

    1973

  5. [5]

    Aller , L. H. 1984, Physics of thermal gaseous nebulae , Vol. 112 (Springer Dordrecht (Dordrecht, Holland: D. Reidel Publishing Company)), https://doi.org/10.1007/978-94-010-9639-3

    doi:10.1007/978-94-010-9639-3 1984

  6. [6]

    1979, , 78, 200

    Alloin, D., Collin-Souffrin, S., Joly, M., & Vigroux, L. 1979, , 78, 200

    1979

  7. [7]

    2010, arXiv e-prints, 1009.2755, 10.48550/arXiv.1009.2755

    Andrae , R. 2010, arXiv e-prints, 1009.2755, 10.48550/arXiv.1009.2755

    arXiv doi:10.48550/arxiv.1009.2755 2010

  8. [8]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, , 93, 5, 10.1086/130766

    doi:10.1086/130766 1981

Show all 104 references
  1. [10]

    2015, , 449, 867, 10.1093/mnras/stv296

    Belfiore , F., Maiolino , R., Bundy , K., et al. 2015, , 449, 867, 10.1093/mnras/stv296

    2015 doi

  2. [11]

    2022, , 659, A26, 10.1051/0004-6361/202141859

    Belfiore, F., Santoro, F., Groves, B., et al. 2022, , 659, A26, 10.1051/0004-6361/202141859

    2022 doi

  3. [12]

    Belley , J., & Roy , J. R. 1992, , 78, 61, 10.1086/191621

    1992 doi

  4. [13]

    A., Pogge , R

    Berg , D. A., Pogge , R. W., Skillman , E. D., et al. 2020, , 893, 96, 10.3847/1538-4357/ab7eab

    2020 doi

  5. [15]

    1998, Galactic Astronomy (Princeton, NJ : Princeton University Press, 1998

    Binney , J., & Merrifield , M. 1998, Galactic Astronomy (Princeton, NJ : Princeton University Press, 1998. (Princeton series in astrophysics))

    1998

  6. [17]

    2009 a , , 700, 309, 10.1088/0004-637X/700/1/309

    Bresolin , F., Gieren , W., Kudritzki , R.-P., et al. 2009 a , , 700, 309, 10.1088/0004-637X/700/1/309

    2009 doi

  7. [18]

    C., & Ryan-Weber , E

    Bresolin , F., Kennicutt , R. C., & Ryan-Weber , E. 2012, , 750, 122, 10.1088/0004-637X/750/2/122

    2012 doi

  8. [19]

    C., & Goddard , Q

    Bresolin , F., Ryan-Weber , E., Kennicutt , R. C., & Goddard , Q. 2009 b , , 695, 580, 10.1088/0004-637X/695/1/580

    2009 doi

  9. [20]

    Cavichia , O., Costa, R. D. D., & Maciel, W. J. 2010, , 46, 159, 10.48550/arXiv.1003.0416

    2010 doi arXiv

  10. [21]

    Cavichia , O., Moll \'a , M., & Baz \'a n , J. J. 2023, , 520, 402, 10.1093/mnras/stad097

    2023 doi

  11. [22]

    Cavichia, O., Mollá, M., Costa, R. D. D., & Maciel, W. J. 2014, , 437, 3688, 10.1093/mnras/stt2164

    2014 doi

  12. [24]

    A., & Rand , R

    Collins , J. A., & Rand , R. J. 2001, , 551, 57, 10.1086/320072

    2001 doi

  13. [25]

    J., & Wyse , R

    Daniel , K. J., & Wyse , R. F. G. 2015, , 447, 3576, 10.1093/mnras/stu2683

    2015 doi

  14. [28]

    C., & Hinkley, D

    Davison, A. C., & Hinkley, D. V. 1997, Bootstrap Methods and their Application, Cambridge Series in Statistical and Probabilistic Mathematics (Cambridge University Press)

    1997

  15. [29]

    A., Kewley , L

    Dopita , M. A., Kewley , L. J., Sutherland , R. S., & Nicholls , D. C. 2016, , 361, 61, 10.1007/s10509-016-2657-8

    2016 doi

  16. [30]

    F., Morisset, C., et al

    Espinosa-Ponce, C., Sánchez, S. F., Morisset, C., et al. 2020, , 494, 10.1093/mnras/staa782

    2020 doi

  17. [31]

    Esteban , C., Carigi , L., Copetti , M. V. F., et al. 2013, , 433, 382, 10.1093/mnras/stt730

    2013 doi

  18. [32]

    Ferguson , A. M. N., & Clarke , C. J. 2001, , 325, 781, 10.1046/j.1365-8711.2001.04501.x

    2001

  19. [33]

    Fitzpatrick, E. L. 1999, , 111, 63, 10.1086/316293

    1999 doi

  20. [35]

    2016, , 462, L41, 10.1093/mnrasl/slw120

    Fragkoudi , F., Athanassoula , E., & Bosma , A. 2016, , 462, L41, 10.1093/mnrasl/slw120

    2016 doi

  21. [36]

    Garnett , D. R. 1998, in Revista Mexicana de Astronomia y Astrofisica Conference Series, Vol. 7, Revista Mexicana de Astronomia y Astrofisica Conference Series, ed. R. J. Dufour & S. Torres-Peimbert , 58

    1998

  22. [37]

    P., Salzer, J

    Giovanelli, R., Haynes, M. P., Salzer, J. J., et al. 1994, , 107, 10.1086/117014

    1994 doi

  23. [38]

    1992, , 262, 455

    Goetz , M., & Koeppen , J. 1992, , 262, 455

    1992

  24. [39]

    M., Cid Fernandes , R., P \'e rez , E., et al

    Gonz \'a lez Delgado , R. M., Cid Fernandes , R., P \'e rez , E., et al. 2016, , 590, A44, 10.1051/0004-6361/201628174

    2016 doi

  25. [40]

    M., & Pérez , E

    González Delgado , R. M., & Pérez , E. 1997, , 108, 199, 10.1086/312950

    1997 doi

  26. [41]

    T., Kudritzki , R.-P., Kewley , L

    Ho , I. T., Kudritzki , R.-P., Kewley , L. J., et al. 2015, , 448, 2030, 10.1093/mnras/stv067

    2015 doi

  27. [42]

    C., Filippenko , A

    Ho , L. C., Filippenko , A. V., & Sargent , W. L. W. 1997, , 487, 579, 10.1086/304642

    1997 doi

  28. [43]

    I., Stasi \'n ska , G., Meynet , G., Guseva , N

    Izotov , Y. I., Stasi \'n ska , G., Meynet , G., Guseva , N. G., & Thuan , T. X. 2006, , 448, 955, 10.1051/0004-6361:20053763

    2006 doi

  29. [44]

    M., Tremonti, C., & et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., & et al. 2003, , 346, 1055, 10.1111/j.1365-2966.2003.07154.x

    2003

  30. [45]

    C., J., Keel , W

    Kennicutt , R. C., J., Keel , W. C., & Blaha , C. A. 1989, , 97, 1022, 10.1086/115046

    1989 doi

  31. [46]

    J., Dopita, M

    Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, , 556, 121, 10.1086/321545

    2001 doi

  32. [47]

    J., & Ellison , S

    Kewley , L. J., & Ellison , S. L. 2008, , 681, 1183, 10.1086/587500

    2008 doi

  33. [49]

    1977, , 218, 333, 10.1086/155687

    Kormendy , J. 1977, , 218, 333, 10.1086/155687

    1977 doi

  34. [50]

    2020, , 2020, 007, 10.1088/1475-7516/2020/02/007

    Krishak , A., Dantuluri , A., & Desai , S. 2020, , 2020, 007, 10.1088/1475-7516/2020/02/007

    2020 doi

  35. [51]

    2019, , 485, 367, 10.1093/mnras/stz366

    Kumari , N., Maiolino , R., Belfiore , F., & Curti , M. 2019, , 485, 367, 10.1093/mnras/stz366

    2019 doi

  36. [52]

    Lacerda , E. A. D., Cid Fernandes , R., Couto , G. S., et al. 2018, , 474, 3727, 10.1093/mnras/stx3022

    2018 doi

  37. [53]

    G., & Fall , S

    Lacey , C. G., & Fall , S. M. 1985, , 290, 154, 10.1086/162970

    1985 doi

  38. [54]

    A., Krumholz , M

    Lopez , L. A., Krumholz , M. R., Bolatto , A. D., Prochaska , J. X., & Ramirez-Ruiz , E. 2011, , 731, 91, 10.1088/0004-637X/731/2/91

    2011 doi

  39. [55]

    F., Lin , L., et al

    L \'o pez-Cob \'a , C., S \'a nchez , S. F., Lin , L., et al. 2022, , 939, 40, 10.3847/1538-4357/ac937b

    2022 doi

  40. [56]

    2019, , 27, 3, 10.1007/s00159-018-0112-2

    Maiolino , R., & Mannucci , F. 2019, , 27, 3, 10.1007/s00159-018-0112-2

    2019 doi

  41. [57]

    A., Rosales-Ortega, F

    Marino, R. A., Rosales-Ortega, F. F., Sánchez, S. F., & et al. 2013, , 559, 10.1051/0004-6361/201321956

    2013 doi

  42. [58]

    Martin , P., & Roy , J. R. 1994, , 424, 599, 10.1086/173917

    1994 doi

  43. [59]

    Martin, P., & Roy , J. R. 1995, , 445, 161, 10.1086/175682

    1995 doi

  44. [60]

    1989, , 239, 885, 10.1093/mnras/239.3.885

    Matteucci , F., & Francois , P. 1989, , 239, 885, 10.1093/mnras/239.3.885

    1989 doi

  45. [61]

    L., Rybski, P

    McCall, M. L., Rybski, P. M., & Shields, G. A. 1985, , 57, 1, 10.1086/190994

    1985 doi

  46. [62]

    2017, , 598, A32, 10.1051/0004-6361/201629525

    M \'e ndez-Abreu , J., Ruiz-Lara , T., S \'a nchez-Menguiano , L., et al. 2017, , 598, A32, 10.1051/0004-6361/201629525

    2017 doi

  47. [63]

    E., Amayo , A., Arellano-C \'o rdova , K

    M \'e ndez-Delgado , J. E., Amayo , A., Arellano-C \'o rdova , K. Z., et al. 2022, , 510, 4436, 10.1093/mnras/stab3782

    2022 doi

  48. [64]

    2010, , 722, 112, 10.1088/0004-637X/722/1/112

    Minchev , I., & Famaey , B. 2010, , 722, 112, 10.1088/0004-637X/722/1/112

    2010 doi

  49. [65]

    I., Cavichia , O., et al

    Mollá , M., Díaz , \'A . I., Cavichia , O., et al. 2019, , 482, 3071, 10.1093/mnras/sty2877

    2019 doi

  50. [66]

    Muggeo , V. M. 2003, Statist. Med., 22, 3055, 10.1002/sim.1545

    2003 doi

  51. [67]

    Narisetty , N. N. 2020, in Handbook of Statistics, Vol. 43, Principles and Methods for Data Science, ed. A. S. R. Srinivasa Rao & C. R. Rao (Elsevier), 207--248, https://doi.org/10.1016/bs.host.2019.08.001

    2020 doi

  52. [68]

    S., Parker, J

    Oey, M. S., Parker, J. S., Mikles, V. J., & Zhang, X. 2003, , 126, 2317, 10.1086/378163

    2003 doi

  53. [70]

    D., Dav \'e , R., Kere s , D., et al

    Oppenheimer , B. D., Dav \'e , R., Kere s , D., et al. 2010, , 406, 2325, 10.1111/j.1365-2966.2010.16872.x

    2010

  54. [71]

    Osterbrock, D. E. 1989, Annals of the New York Academy of Sciences, 571, 99, 10.1111/j.1749-6632.1989.tb50500.x

    1989

  55. [72]

    E., & Ferland , G

    Osterbrock , D. E., & Ferland , G. J. 2006, Astrophysics of gaseous nebulae and active galactic nuclei (Sausalito, California, USA: University Science Books), 461 p

    2006

  56. [73]

    Pagel , B. E. J., Edmunds , M. G., Blackwell , D. E., Chun , M. S., & Smith , G. 1979, , 189, 95, 10.1093/mnras/189.1.95

    1979 doi

  57. [74]

    Pagel , B. E. J., Simonson , E. A., Terlevich , R. J., & Edmunds , M. G. 1992, , 255, 325, 10.1093/mnras/255.2.325

    1992 doi

  58. [75]

    1895, Proceedings of the Royal Society of London Series I, 58, 240

    Pearson , K. 1895, Proceedings of the Royal Society of London Series I, 58, 240

  59. [76]

    1969, Boletin de los Observatorios Tonantzintla y Tacubaya, 5, 3

    Peimbert , M., & Costero , R. 1969, Boletin de los Observatorios Tonantzintla y Tacubaya, 5, 3

    1969

  60. [78]

    Pettini, M., & Pagel, B. E. J. 2004, , 348, L59–L63, 10.1111/j.1365-2966.2004.07591.x

    2004

  61. [79]

    2021, Journal of Open Source Software, 6, 3859, 10.21105/joss.03859

    Pilgrim, C. 2021, Journal of Open Source Software, 6, 3859, 10.21105/joss.03859

    2021 doi

  62. [80]

    S., Grebel , E

    Pilyugin , L. S., Grebel , E. K., Zinchenko , I. A., et al. 2018, , 613, A1, 10.1051/0004-6361/201732185

    2018 doi

  63. [81]

    1997, , 321, 111

    Prugniel , P., & Simien , F. 1997, , 321, 111

    1997

  64. [82]

    D., van Driel , W., & Jog , C

    Qu , Y., Di Matteo , P., Lehnert , M. D., van Driel , W., & Jog , C. J. 2011, , 535, A5, 10.1051/0004-6361/201116502

    2011 doi

  65. [83]

    C., Minchev , I., Bland-Hawthorn , J., & Haywood , M

    Quillen , A. C., Minchev , I., Bland-Hawthorn , J., & Haywood , M. 2009, , 397, 1599, 10.1111/j.1365-2966.2009.15054.x

    2009

  66. [84]

    J., Sterling , N

    Reynolds , R. J., Sterling , N. C., Haffner , L. M., & Tufte , S. L. 2001, , 548, L221, 10.1086/319119

    2001 doi

  67. [86]

    P., Quinn , T

    Ro s kar , R., Debattista , V. P., Quinn , T. R., & Wadsley , J. 2012, , 426, 2089, 10.1111/j.1365-2966.2012.21860.x

    2012

  68. [87]

    Roy , J. R. 1996, in Astronomical Society of the Pacific Conference Series, Vol. 91, IAU Colloq. 157: Barred Galaxies, ed. R. Buta , D. A. Crocker , & B. G. Elmegreen , 63

    1996

  69. [88]

    S \' a nchez, S. F. 2006, Astronomische Nachrichten, 327, 850, 10.1002/asna.200610643

    2006 doi

  70. [89]

    F., Rosales-Ortega , F

    S \'a nchez , S. F., Rosales-Ortega , F. F., Marino , R. A., & et al. 2012, , 546, A2, 10.1051/0004-6361/201219578

    2012 doi

  71. [90]

    F., P \'e rez , E., Rosales-Ortega , F

    S \'a nchez , S. F., P \'e rez , E., Rosales-Ortega , F. F., et al. 2015, , 574, A47, 10.1051/0004-6361/201424873

    2015 doi

  72. [91]

    K., & Risaliti , G

    Sani , E., Marconi , A., Hunt , L. K., & Risaliti , G. 2011, , 413, 1479, 10.1111/j.1365-2966.2011.18229.x

    2011

  73. [92]

    Scarano, S., Madsen, F. R. H., Roy, N., & Lépine, J. R. D. 2008, , 386, 963–972, 10.1111/j.1365-2966.2008.13079.x

    2008

  74. [93]

    1971, , 168, 327, 10.1086/151090

    Searle , L. 1971, , 168, 327, 10.1086/151090

    1971 doi

  75. [94]

    A., & Binney , J

    Sellwood , J. A., & Binney , J. J. 2002, , 336, 785, 10.1046/j.1365-8711.2002.05806.x

    2002

  76. [95]

    2013, , 558, A43, 10.1051/0004-6361/201322062

    Singh , R., van de Ven , G., Jahnke , K., et al. 2013, , 558, A43, 10.1051/0004-6361/201322062

    2013 doi

  77. [96]

    Stasi \'n ska , G., Cid Fernandes , R., Mateus , A., Sodré , L., & Asari , N. V. 2006, , 371, 972, 10.1111/j.1365-2966.2006.10732.x

    2006

  78. [97]

    2008, , 391, L29, 10.1111/j.1745-3933.2008.00550.x

    Stasi \'n ska , G., Vale Asari , N., Cid Fernandes , R., et al. 2008, , 391, L29, 10.1111/j.1745-3933.2008.00550.x

    2008

  79. [98]

    Storchi-Bergmann , T., Calzetti , D., & Kinney , A. L. 1994, , 429, 572, 10.1086/174345

    1994 doi

  80. [99]

    F., García-Benito , R., Zibetti , S., & et al

    Sánchez , S. F., García-Benito , R., Zibetti , S., & et al. 2016, , 594, A36, 10.1051/0004-6361/201628661

    2016 doi

  81. [100]

    F., Kennicutt, R

    Sánchez, S. F., Kennicutt, R. C., de Paz, A. G., & et al. 2012, , 538, A8, 10.1051/0004-6361/201117353

    2012 doi

  82. [101]

    F., Rosales-Ortega, F

    Sánchez, S. F., Rosales-Ortega, F. F., Iglesias-Páramo, J., & et al. 2014, , 563, A49, 10.1051/0004-6361/201322343

    2014 doi

  83. [102]

    F., Pérez, I., & et al

    Sánchez-Menguiano, L., Sánchez, S. F., Pérez, I., & et al. 2016, , 587, A70, 10.1051/0004-6361/201527450

    2016 doi

  84. [103]

    F., Pérez, I., et al

    Sánchez-Menguiano, L., Sánchez, S. F., Pérez, I., et al. 2018, , 609, A119, 10.1051/0004-6361/201731486

    2018 doi

  85. [104]

    S., Cid Fernandes , R., et al

    Vale Asari , N., Couto , G. S., Cid Fernandes , R., et al. 2019, , 489, 4721, 10.1093/mnras/stz2470

    2019 doi

  86. [105]

    B., & Edmunds , M

    Vila-Costas , M. B., & Edmunds , M. G. 1992, , 259, 121, 10.1093/mnras/259.1.121

    1992 doi

  87. [107]

    1996 b , , 280, 720, 10.1093/mnras/280.3.720

    ---. 1996 b , , 280, 720, 10.1093/mnras/280.3.720

    1996 doi

  88. [108]

    Vogt , F. P. A., Dopita , M. A., Kewley , L. J., et al. 2014, , 793, 127, 10.1088/0004-637X/793/2/127

    2014 doi

  89. [109]

    Vogt , F. P. A., P \'e rez , E., Dopita , M. A., Verdes-Montenegro , L., & Borthakur , S. 2017, , 601, A61, 10.1051/0004-6361/201629853

    2017 doi

  90. [110]

    J., Lamareille , F., Vergani , D., & et al

    Walcher , C. J., Lamareille , F., Vergani , D., & et al. 2008, , 491, 713, 10.1051/0004-6361:200810704

    2008 doi

  91. [111]

    J., Wisotzki, L., Bekeraité, S., & et al

    Walcher, C. J., Wisotzki, L., Bekeraité, S., & et al. 2014, , 569, A1, 10.1051/0004-6361/201424198

    2014 doi

  92. [112]

    Zaritsky, D., Kennicutt, R. C. J., & Huchra, J. P. 1994, , 420, 87, 10.1086/173544

    1994 doi

  93. [113]

    A., Just , A., Pilyugin , L

    Zinchenko , I. A., Just , A., Pilyugin , L. S., & Lara-Lopez , M. A. 2019, , 623, A7, 10.1051/0004-6361/201834364

    2019 doi

  94. [114]

    A., Pilyugin , L

    Zinchenko , I. A., Pilyugin , L. S., Grebel , E. K., S \'a nchez , S. F., & V \' lchez , J. M. 2016, , 462, 2715, 10.1093/mnras/stw1857

    2016 doi

  95. [115]

    2021, , 500, 2359, 10.1093/mnras/staa2246

    Zurita , A., Florido , E., Bresolin , F., P \'e rez-Montero , E., & P \'e rez , I. 2021, , 500, 2359, 10.1093/mnras/staa2246

    2021 doi

  96. [116]

    Zurita , A., Rozas , M., & Beckman , J. E. 2000, , 363, 9

    2000

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.