the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Oct 2024
Discordance Dating: A New Approach for Dating Sedimentary Alteration Events
Abstract. Zircon is the premier geochronometer used to date igneous and metamorphic processes, constrain sediment provenance, and monitor key events in Earth history such as the growth of continents and the evolution of the biosphere. Zircon U-Pb systematics can be perturbed by the loss or gain of uranium and/or lead, which can result in disagreement between the apparent radiometric ages of the two U-Pb decay systems – a phenomenon that is commonly termed ‘discordance’. Discordance in zircon can be difficult to reliably interpret and therefore discordant data are traditionally culled from U-Pb isotopic datasets, particularly detrital zircon datasets. Here we provide a data reduction scheme that extracts reliable age information from discordant zircon U-Pb data found in detrital zircon suites, tracing such processes as fluid flow or contact metamorphism. We provide the template for data reduction and interpretation, a suite of sensitivity tests using synthetic data, and ground-truth this method by analyzing zircons from the well-studied Alta Stock metamorphic aureole. Our results show accurate quantification of a ~23 Ma in situ zircon alteration event that affected 1.0–2.0 Ga detrital zircons in the Tintic quartzite. The ‘discordance dating’ method outlined here may be widely applicable to a variety of detrital zircon suites where pervasive fluid alteration or metamorphic recrystallization has occurred, even in the absence of concordant U-Pb data.
- Preprint
(1730 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on gchron-2024-27', Axel Schmitt, 03 Feb 2025
This contribution is about the potential of detrital zircon U-Pb dates to record geologic events that overprinted zircon and caused partial to near-complete Pb-loss, resulting in discordance. Such discordant detrital zircon data are usually discarded, whereas Reimink et al. convincingly argue that such data can reveal geologically meaningful lower concordia intercept ages. A numerical model is introduced, building on Reimink et al. (2016), and tested against a real-world data set for detrital zircon from a quartzite which was thermally overprinted in a magmatic contact aureole.
Judging from the success of Reimink et al. (2016), which was designed to extract meaningful formation ages from discordant detrital zircon data sets and is frequently cited, I find this approach promising. Interrogating detrital zircon for their potential of revealing geological episodes capable of producing Pb-loss would circumvent culling of significant amounts of data and allow gaining useful insights from zircon domains usually not targeted for high spatial resolution analysis due to their non-ideal structure (e.g., rims, cracks, etc.). The quality of the writing and the artwork are at a high level, and the scope of the work is a perfect match for GEOCHRONOLOGY.
One suggestion for improvement is adding an explanation about the lower age limit of this approach. The manuscript clearly states that older primary ages permit more precise identification of discordance, but it does not specify the lower age limits. Discordance in Phanerozoic detrital zircon ages is typically difficult to discern in LA-ICP-MS or SIMS data, and 207Pb/206Pb ages required as input in the model will have high uncertainties. I tested the model with the link provided on the Ulusoy et al. (2019) dataset, and it did not produce the expected zero-age intercept for heating during a Holocene eruption.
Potential mechanisms which produce Pb-loss in zircon are discussed. The authors specifically address recrystallization/overgrowth vs. fluid induced leaching for their sample data considering correlative trace element data. Although they are correct that identifying the Pb-loss mechanism is difficult and may require different tools on a case-by-case basis, it would be helpful to provide a bit more context by discussing other zircon-based dating methods targeting sediment evolution (e.g., in-situ dating of xenotime overgrowths, U-Th/He geochronology, Raman dating, or fission tracks; see additional reference list). If possible, it would be useful to quantify the thermal regime for which this new discordia-lower-intercept geochronometer/thermochronometer is sensitive, for example by calculating model closure temperatures for volume diffusion (e.g., for Pb in metamict zircon; Geisler et al., 2002) and comparing these to those of alternative methods mentioned above.
In the list of processes suspected of causing discordance (Lines 69–76), I would also include pyrometamorphic heating for completeness. Zircon in crustal volcanic xenoliths or contact rocks when sufficiently heated can also be (partially) reset; this has been utilized by (U-Th)/He dating (Cooper et al., 2011), and concomitant Pb-loss has also been documented (Ulusoy et al. 2019).
Providing an easy-to-use portal for the numerical model is a welcome service to the community. When testing it, however, I missed an output value for the lower intercept age and its uncertainties.
Some additional suggestions for improvement and minor corrections are provided point-by-point.
Line 32: Please write “U-Th-Pb” as the Schaltegger et al. (2015) also reviews U-Th disequilibrium dating.
Line 35: Please check references for completeness; none of the three references cited here were found in the reference list.
Line 64: Micron = not SI; should be micrometre
Line 75: Pyrometamorphic heating of xenocrysts/xenoliths is another process (Ulusoy et al., 2019).
Line 98: It would be helpful to explicitly state the formula for calculating discordance here, as it was done in Reimink et al. (2016).
Line 114: The discordance method can be seen as complementary to (U-Th)/He dating or other methods in its ability to extract thermally or fluid induced alteration of sediments. Mentioning these alternative approaches would provide valuable context.
Line 150: Something is missing here.
Line 165: Here and elsewhere: ranges should be indicated by the “en dash”.
Line 192: “and“ after 1800 Ma?
Line 150: Why 150? Please justify.
Line 277: Isn’t this a logical consequence of each probability curve being normalized to an area of unity?
Line 354: Space between number and unit.
Line 398: Use official name SRM 612 (https://tsapps.nist.gov/srmext/certificates/612.pdf)
Line 398: When comparing data for the 91500 secondary reference zircon to literature values, some discrepancies are noted. Campbell et al. (2014), for example, state 11 +- 3 µg/g Al in 91500 (1se), whereas the average from the supplement is only half that value (5.7 +- 0.19 µg/g Al). Notably, there is also significant scatter in the data (MSWD = 5.1). The discrepancy is even more severe for Ca, for which literature values are 1.9 +- 0.6 µg/g (Coble et al., 2018) whereas the average for the data in the supplement is 35 µg/g (with in part very large uncertainties and even negative values). Iron in 91500 zircon, by contrast, is lower in the supplementary data compared to the literature (1.71 vs. 3.4 µg/g; Coble et al., 2018). I am suspicious about these elements being major components in NIST SRM 612 glass (except for Fe): Al and Ca are present at ~2 and ~12 wt.% (oxide) levels. How much of a matrix effect does this introduce when NIST SRM 612 is used as the trace element primary reference material for zircon? If trace element data are inaccurate for zircon, then raw ratios should be used, which would serve the same purpose. Please also remove negative values from the supplementary table and state corresponding detection limits.
Line 401: Please address why the 207Pb/206Pb values for NIST SRM 612 appear to be significantly lower than reference values reported in the literature (0.8995 vs. 0.907; Woodhead and Hergt, 2001)? Also, there are several outliers for run IDs between 500 and 531. How does this affect the robustness of the zircon 207Pb/206Pb results analysed under these conditions?
Line 403: Spelling: Peixe (here and elsewhere)
Line 449: between … and
Line 464: In Fig. 7, please state a value and an uncertainty for the discordance date.
Line 523: Fig. 9 preferable µg/g instead of ppm (cosmetics: superscript in panel C).
Line 526: Al-in-zircon as a tracer for discordance is interesting, and a bit surprising as Al is comparatively fluid immobile. The dissolution-reprecipitation scenario for metamict zircon invokes amorphous phases in recrystallized zircon as sinks not only for Al, but also Ca and Fe (e.g., Geisler et al., 2007). It is hence unexpected that Ca and Fe seemingly do not share the trend for Al. In the light of the deviations of the reported values for secondary references from literature values (see comment for line 398), could you please comment if such variability could have gone undetected?
Line 547: Please explain how alpha dose was calculated.
Line 582: The first column is difficult to understand; can the percentiles be separated from the classes, and be directly shown with their respective columns?
Line 632: Please add degree symbol. This would also be the place to discuss the thermal sensitivity (“closure temperature”) of different chronometers applicable to zircon.
Line 641: “to use” seems superfluous
Line 668: Please use abbreviations that are consistent with the author list.
Additional references
Campbell, L. S., Compston, W., Sircombe, K. N., & Wilkinson, C. C. (2014). Zircon from the East Orebody of the Bayan Obo Fe–Nb–REE deposit, China, and SHRIMP ages for carbonatite-related magmatism and REE mineralization events. Contributions to Mineralogy and Petrology, 168, 1-23.
Coble, M. A., Vazquez, J. A., Barth, A. P., Wooden, J., Burns, D., Kylander‐Clark, A., ... & Vennari, C. E. (2018). Trace element characterisation of MAD‐559 zircon reference material for ion microprobe analysis. Geostandards and Geoanalytical Research, 42(4), 481-497.
Geisler, T., Schaltegger, U., & Tomaschek, F. (2007). Re-equilibration of zircon in aqueous fluids and melts. Elements, 3(1), 43-50.
Geisler, T., Ulonska, M., Schleicher, H., Pidgeon, R. T., & van Bronswijk, W. (2001). Leaching and differential recrystallization of metamict zircon under experimental hydrothermal conditions. Contributions to Mineralogy and Petrology, 141(1), 53-65.
McNaughton, N. J., Rasmussen, B., & Fletcher, I. R. (1999). SHRIMP uranium-lead dating of diagenetic xenotime in siliciclastic sedimentary rocks. Science, 285(5424), 78-80.
Reiners, P. W., Campbell, I. H., Nicolescu, S., Allen, C. M., Hourigan, J. K., Garver, J. I., ... & Cowan, D. S. (2005). (U-Th)/(He-Pb) double dating of detrital zircons. American Journal of Science, 305(4), 259-311.
Woodhead, J. D., & Hergt, J. M. (2001). Strontium, neodymium and lead isotope analyses of NIST glass certified reference materials: SRM 610, 612, 614. Geostandards Newsletter, 25(2‐3), 261-266.
Ulusoy, I., Sarıkaya, M. A., Schmitt, A. K., Şen, E., Danišík, M., & Gümüş, E. (2019). Volcanic eruption eye-witnessed and recorded by prehistoric humans. Quaternary Science Reviews, 212, 187-198.
Citation: https://doi.org/10.5194/gchron-2024-27-RC1 -
RC2: 'Comment on gchron-2024-27', Ryan Ickert, 05 Mar 2025
Review of “Discordance Dating: A New Approach for Dating Sedimentary Alteration Events” by Reimink et al. for Geochronology.
This review is by Ryan Ickert (Purdue University)
In this manuscript, the authors do the following:
- Present a modification (section 2.1) to an algorithm introduced in a prior publication (Reimink et al., 2016) so that “lower intercept U-Pb concordia” data can be inverted from discordant sets of U-Pb measurements. They ground-truth the algorithm using a suite of synthetic datasets (section 2.2).
- They apply this algorithm (section 3) to a suite of detrital zircon data from a Cambrian clastic rock affected by a well constrained Oligocene-Miocene (~25-23 Ma) magmatic and hydrothermal event. Inverting the highly discordant array of zircon U-Pb data recovers a ca. 25 Ma date.
- They describe trace element and imaging data collected on the zircon (section 3.3), and speculate on its utility for inferring discordance inducing processes.
The manuscript is well-written, clear, contains high quality geochemical and isotopic data, and has good figures, although in the PDF the figures are quite small and difficult to read. I assume that in a final typeset form this would be rectified. The modification to the 2016 manuscript should be useful.
Since the manuscript is so generally well written, I only have large-scale “substantive” comments.
***Manuscript length***
The manuscript is too lengthy and should be a “short communication” or a “technical note”. The heart of it is a modest, straightforward (but useful!) modification of a technique introduced in a 2016 paper. The introduction is a suite of boilerplate “zircon is a good mineral” text, and the entirety of Section 3.3 has no bearing on the conclusions drawn in Section 3.1/3.2 and is not referenced in the abstract. The trace element/imaging data in Section 3.3 is interesting and the authors have obviously put a lot of thought into it but unfortunately -as they make clear – the results provide no real insights. If the authors would like to infer process from trace element data from discordant zircon, I would like to read that, but it should be a different manuscript. I strongly recommend cutting section 3.3 (the rest of the manuscript would read the same with no editing, including the abstract, introduction, and conclusion), and compressing the introductory material (it’s just a list with no literature synthesis) and if needed, moving some or all of section 2.2 and 3.2 to a supplement.
***Singular discordance events***
The passage on line 108-113 describes a critical assumption for this technique:
“…one useful assumption can safely be applied: after the deposition of the sediment, all the zircon grains have a shared thermal and geological history. In this study we leverage this assumption that post depositional U-Pb isotopic discordance may affect all zircon grains within a given sediment at the same time, in order to use discordant detrital zircon U-Pb data to investigate post-depositional geologic events.”
This is clearly a safe assumption for the Alta example here, where there is overwhelming geological, geochemical, and geochronological evidence for a massive ca. 25 Ma event. It’s unclear to me that this might be equally true for sample suites with different histories, including and especially those without such a strong, singular event. The key assumption here is that each individual measured chronometer responds in the same way to the shared geological history, and it’s one that I suspect is not correct. Individual grains, particularly detrital grains, will have different sizes, alpha-parent concentrations, alpha-dose histories, and annealing histories and will each have different susceptibility to geological events. For example, fluid flow is likely to be highly protracted, and different grains are likely to respond differently, or not at all, in a manner corresponding to their local environment and history. One grain might record an event at one point because it is associated with a vein and fluid flow, then it might seal, and millions (or 10s of millions etc.) of years later a different event occurs to a different grain. Protracted uranium uptake is well documented in for example, in the literature of U-daughter product geochronology of low temperature phosphate and carbonates (a good example is some of the U-Pb data in the supplement to Fassett et al. 2011 https://doi.org/10.1130/G31466.1).
This is not to say this isn’t a useful technique, but the authors are presenting, in my opinion, an inadvertently misleading characterization of the applicability of the assumption listed on lines 108-113.
***Decay Constants***
There is a subtle but important issue here, having to do with decay-constant uncertainties.
When single decay constants are used, and used in the same manner (for example comparing two 206/238 dates from concordant analyses) the decay constant uncertainties are very highly correlated and are typically negligible. This is the basis for ignoring such so-called “systematic” uncertainties when comparing dates from the same isotopic system. However, when mixing decay constants, and using them in what are effectively different proportions, they can no longer be neglected, and when looking at concordia “chords”, can be surprisingly large.
To frame the issue differently, if you compare a 206/238 date to another 206/238 date, you almost certainly can neglect decay-constant uncertainties on the difference between the two dates. If you compare a 207/235 date to a 206/238 date, you cannot neglect them. If you compare a 206/238 to a 207/206 date, you cannot neglect the decay constant uncertainties, but they are not independent because they both use the 238U decay rate. Upper and lower intercept concordia dates each have a unique “mixture” of both decay rates and so cannot be neglected except when comparing them with very similar (e.g., subparallel) chords.
In the dataset presented here, because of the young age of the lower intercept and the old age of most of the grains, the decay constant uncertainties are negligible. But since this is meant to be a useful technique for future work, this may actually matter a great deal, particularly with early paleozoic and older, lower intercepts, where decay constant uncertainties when compared to say, 206/238 dates, can be 10s of Ma.
Geometrically, it’s easy to see when this will matter – as the slope of the chord near the intercept (lower or upper) becomes more parallel, the date will “smear” more within the uncertainty band around the concordia. Having folks use this tool without a method to address this potentially significant source of uncertainty would be dangerous.
Unfortunately, it can be a bit complicated to address because it depends on the date you want to compare it to. The decay constant uncertainty in the difference between a lower intercept and a 206/238 date is different than when comparing it to a 207/235 date (or a 207/206 date, or an intercept with a different slope etc.). However, the calculation is straightforward to do numerically and could easily be incorporated into the code.
Citation: https://doi.org/10.5194/gchron-2024-27-RC2 -
RC3: 'Comment on gchron-2024-27', Chris Kirkland, 07 Mar 2025
This study continues the concept of extracting age information from discordant zircon U-Pb data, particularly in detrital zircon suites. Traditional geochronology often discards discordant data, but this approach leverages discordance to date post-depositional geological events like fluid alteration and contact metamorphism. The paper applies a technique introduced by Reimink in 2016. The method is validated using synthetic data and applied to zircons from the Alta Stock metamorphic aureole, successfully dating a ~23 Ma alteration event. This technique should have implications for dating fluid flow, low-temperature metamorphism, and sedimentary basin evolution.
Introduction & Framing
The study builds upon Reimink et al. (2016) by introducing a useful refinement to an existing core technique. As such, it may be more effectively presented as a technical note that directly highlights the specific methodological improvement. Specifically, I am not convinced that the introduction needs to be structured with the basic conceptual framework of U-Pb geochronology and its uses. I would have thought that most / all readers of this journal would be well informed of the basic concepts. Also, there are elements of similarity with some previous works on the subject area starting the work in this way. In any case, I think it would be more efficient and productive for this work to be more direct about inverting discordant data to better understand its effect. So, in short, the work could commence around line 78 without any determent to the new insight the work aims to convey.How the Study Represents the Field
I am concerned that the general depiction of the field, as not aiming to use discordant data, is not an accurate portrayal of the current community knowledge. Please let me elaborate on this: U-Pb discordance has long been know and modelled via discordia regressions and their lower intercepts interpreted with various success as the times of meaningful geological events. Clearly with additional scatter from a single Pb loss line interpretation of the timing of radiogenic Pb mobility becomes difficult if not impossible to determine using conventional regression approaches. However, as I am sure the authors are well-aware there is now a wide range of works that have proposed methods to address this complexity and extract meaningful times for Pb loss. Specifically, the following works all introduce methods to invert discordant data to resolve Pb loss times.
Sharman, G. R., & Malkowski, M. A. (2024). Modeling apparent Pb loss in zircon U–Pb geochronology. Geochronology, 6(1), 37-51. https://doi.org/10.5194/gchron-6-37-2024
Morris, G. A., Kirkland, C. L., & Pease, V. (2015). Orogenic paleofluid flow recorded by discordant detrital zircons in the Caledonian foreland basin of northern Greenland. Lithosphere, 7(2), 138-143. https://doi.org/10.1130/L420.1
Kirkland, C. L., Abello, F., Danišík, M., Gardiner, N. J., Spencer, C., & (2017). Mapping temporal and spatial patterns of zircon U-Pb disturbance: A Yilgarn Craton case study. Gondwana Research, 52, 39-47. https://doi.org/10.1016/j.gr.2017.08.004 747
Kirkland, C. L., Johnson, T. E., Kinny, P. D., Kapitany, T., & (2020). Modelling U-Pb discordance in the Acasta Gneiss: Implications for fluid–rock interaction in Earth's oldest dated crust. Gondwana Research, 77, 223-237. https://doi.org/10.1016/j.gr.2019.07.017
My point simply is that a lot of emphasis is being placed on the term “most” in the statement “most modern U-Pb studies aim to minimize its effect rather than understand or use it”.
Nothing would be lost from the advance this work makes by better framing it in the context of the existing field working on exactly the problem addressed in this paper.
So, it would seem reasonable to also acknowledge there are a range of other techniques which also aim to invert discordant data to arrive at the most likely time of radiogenic-Pb mobility. Providing this context would better frame the advance of this work.Methodological comments
I am not convinced that the statement in line 96 is accurate “Without the constraint of a single, shared geologic history, no discordant datum can be confidently related to another datum, whether it is discordant or concordant.” As shown from other works seeking to invert discordant data the reality is that discordant data is, more often than not, derived (in your words “related to”) from the same geological provenance (e.g. discordant data and concordant data is ultimately derived from terranes that share one or more connected formation ages). This connection can be probabilistically assessed and used in the inversion problem.
Line 98, the concept of “strict” or not in terms of discordance is a bit nebulous and would be better framed as within or outside the analytical confidence bounds.
Line 101 the paper at this stage in the text now reverts to acknowledge that there are other approaches to invert discordant data. This creates a bit of a non sequitur with what was introduced around line 80. Also, the list of works focused on this topic is curiously incomplete. I would have thought that the author would have been familiar with the work on Acasta that uses Pb loss modelling to derive most likely times of fluid-rock interaction? While the method is contrasted against linear regression approaches (e.g., IsoplotR), other discordance modelling techniques (e.g., isotope diffusion modelling, Bayesian approaches) are not considered. A discussion on how this method compares would strengthen its utility.
The description of the Concordance-Discordance-Comparison technique (and its inverse in Olierook) is incomplete, as it is not merely a projection method. Instead, it employs a Bayesian Monte Carlo approach to probabilistically evaluate all possible Pb loss events, ultimately determining the most likely Pb loss age (or the primary crystallization age in the inverse application).
Line 108, the work states a “safe” assumption is that “all the zircon grains have a shared thermal and geological history” yet is this really the case. Specifically, other works have clearly demonstrated (that in some cases) the susceptibility of the zircon cargo to post crystallization modification is highly variable. This is easily demonstrated by considering the heterogenous alpha dose (or U content) within any detrital zircon population. Effectively, this means that in many situations, components within a chemically heterogeneous zircon population will be “blind” to certain events whereas other grains may record that event. This assumption, that all zircons will respond to the same event, at least needs to be discussed and considered as it has fundamental implications for when the proposed methodology would be the most effective or not.
Line 120-122 is a statement I would certainly agree with and has been said various times before, so you probably could support your point with references. “…..enables geochronologists to extract meaningful geological information from discordant datasets, turning previously discarded data into valuable insights” Mathieson et al., 2024. Turning Trash into Treasure: Extracting Meaning from Discordant Data via a Dedicated Application. G4 in press, 2024. DOI: 10.22541/essoar.173315682.28715367/v1. “CDC modelling of discordant U-Pb zircon analyses may provide a means to recognise the distal footprint of otherwise difficult to date tectonothermal events and extract useful information from often discarded analyses.” https://doi.org/10.1016/j.gr.2017.08.004
The work may be improved by considering that discordance in the case study dataset could also relate to physical mixtures (e.g. core-rims).
The text on many of the figures is illegible (this may just be an issue with the review pdf but the scaling of text especially in figure 2 needs to be made more consistent across the different components of the figure).
Line 294, it would be more informative to know how it performs relative to Sharman, G. R., & Malkowski, M. A. (2024) and the Concordance-Discordance-Comparison test, rather than against linear regression approaches which clearly are not designed to deal with such over dispersion.
It would be useful to have a more complete consideration / discussion of how uncertainty in the inversion method has been dealt with. Presumably this is a function of the step size the trial cords have been spaced at? The method relies on a summed-likelihood approach, but it is unclear how it handles data gaps, outliers, or clustering effects. Could certain grain populations disproportionately influence the results?
Line 265-266 “and therefore yields more accurate results for complex datasets” more accurate than what? Linear regression? Well obviously, it must, as it is designed to account for dispersion in the data. More accurate than the other Pb loss modelling approaches? I would be rather confident in guessing that the answer to that question depends entirely on the underlying geological controls on the dispersion e.g. chemically heterogeneous grains (with heterogeneous age) variably responding to different episodes of Pb loss or chemically homogeneous grains (with heterogeneous ages) undergoing a single phase of Pb loss. The assumption that all zircons in a sedimentary unit share a common post-depositional history is not universally valid. Localized alteration, differential Pb mobility, or variable zircon radiation damage could result in multiple resetting events rather than a single event. How does the method account for this?
The model assumes that the youngest discordant grains define the resetting event. However, zircon discordance can result from multiple overlapping processes (fluid mobility, radiation damage, Pb clustering). It would be nice if the paper could clarify how, it differentiates true geologic resetting from more complex Pb-loss mechanisms.
While synthetic datasets were tested, real-world zircon populations may exhibit more complex discordance patterns than the simplified scenarios presented. A more robust sensitivity analysis including mixed multi-stage alteration histories could improve confidence in the method. A test case where the method is applied to a sample with known independent constraints (e.g., metamorphic zircon rim ages) would validate its accuracy.
The discussion on whether Pb loss is due to fluid infiltration versus recrystallization is a bit speculative without clear microstructural evidence (e.g., TEM, Raman spectroscopy). Suggest incorporating or citing complementary methods that could distinguish these processes.
The analytical dataset appears to be of generally high quality, although I note the 207/206Pb values for glass NIST 612 appear a bit low.Citation: https://doi.org/10.5194/gchron-2024-27-RC3
Data sets
Reference Material and Sample Zircon U-Pb-TE datasets Jesse R. Reimink, Renan Beckman, Erik Schoonover, Max Lloyd, Joshua Garber, Joshua H. F. L. Davies, Alexander Cerminaro, Morgann G. Perrot, and Andrew J. Smye https://doi.org/10.5281/zenodo.13972611
Model code and software
Modeling code for discordance dating Jesse R. Reimink, Renan Beckman, Erik Schoonover, Max Lloyd, Joshua Garber, Joshua H. F. L. Davies, Alexander Cerminaro, Morgann G. Perrot, and Andrew J. Smye https://doi.org/10.5281/zenodo.13972611
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 353 | 70 | 97 | 520 | 12 | 10 |
- HTML: 353
- PDF: 70
- XML: 97
- Total: 520
- BibTeX: 12
- EndNote: 10
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1