Astrophysics Wrapped 2025: Year-in-Review of Every Astrophysics arXiv Paper from 2025

Amruth Alfred; Hetansh Shah; Rommulus Francis Lewis

REVIEW 5 major objections 5 minor 1 cited by

This paper provides a complete census of all 18,660 astrophysics preprints posted in 2025 and uses them to map the field's topics, instruments, collaborations, citations, and publishing costs.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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

T0 review · deepseek-v4-flash

2026-08-03 00:09 UTC pith:THENSXNK

load-bearing objection Useful descriptive census of 2025 astro-ph, but the telescope ranking is known-wrong by the authors' own LIGO check, and the promised spectral fingerprint is missing. the 5 major comments →

arxiv 2602.12303 v3 pith:THENSXNK submitted 2026-02-11 astro-ph.IM astro-ph.COastro-ph.EPastro-ph.GAastro-ph.SR

Astrophysics Wrapped 2025: Year-in-Review of Every Astrophysics arXiv Paper from 2025

Rommulus Francis Lewis , Hetansh Shah , Amruth Alfred This is my paper

classification astro-ph.IM astro-ph.COastro-ph.EPastro-ph.GAastro-ph.SR

keywords astrophysicsbibliometricsscientometricsresearch trendstelescope statisticscollaborationopen accesspreprint server

verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper sets out to be a complete year-in-review of every astrophysics preprint posted in 2025, turning 18,660 titles, abstracts, citations, and author affiliations into a series of whole-field statistics. It claims to identify what the community actually studied—most-mentioned telescopes, top keywords and subfields, most-analyzed objects from gravitational-wave events to exoplanets—and how it collaborated geographically, what it paid to publish, and how citations concentrate. A sympathetic reader would care because this is a rare quantitative snapshot of an entire discipline in one year: which instruments and objects dominate attention, which papers become citation magnets, and where the world's research is produced. The authors hope the statistics help students and professionals see where the field is heading.

Core claim

The central claim is that this report provides a complete, high-fidelity dataset of all papers uploaded to the astrophysics section of the preprint server during 2025, with a unique set of metrics derived from each paper's metadata. Using daily collection of new submissions, the authors count 18,660 papers, up from 16,333 the previous year. They compute citation indices per paper, per telescope, per keyword, per subfield, and per journal; they define four collaboration indices to characterize how local or international research teams are; they estimate the total cost of publishing fees; and they present a first-of-its-kind spectral fingerprint showing how research is distributed across the e

What carries the argument

The carrying mechanism is a set of hand-built name lists—about 40 telescopes, roughly 100 subfields, keywords, and object-nomenclature patterns such as 'GW' plus six digits, Messier/NGC patterns, and exoplanet naming conventions—matched by string matching against every paper's title and abstract. To make comparisons quantitative, the paper defines four collaboration indices (Local Collaborative Index, Local Collaborative Ratio, Global Collaborative Index, Non-repeated Global Collaborative Index) and four citation indices (All Articles Citation, Journal Articles Citation, Excluding-Self variants), which together let the authors rank categories by how often they are cited and how locally or in

Load-bearing premise

The load-bearing premise is that matching hand-built lists of telescope and object names against titles and abstracts faithfully captures what a paper studies or which instrument it uses; the authors themselves call this 'not the most robust way' and report a false positive in which an Apple M1 chip was counted as Messier 1.

What would settle it

Take a random sample of 200 papers, read their full text, and compare each paper's telescope and object mentions with the string-matching result; if the discrepancy rate exceeds a few percent, the rankings would be unreliable. The paper's own M1-as-Messier-1 example shows the test is sensitive enough to detect such errors.

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

If this is right

Field output rose to 18,660 new astrophysics preprints in 2025, with September and October the most productive months.
JWST was the most-mentioned telescope, while Einstein Probe and LIGO papers had the highest citation averages; the gravitational-wave community concentrated on a small number of events, while the exoplanet community spread across 512 different objects.
About 80% of the year's preprints eventually appear in a journal, with Astronomy and Astrophysics, the Astrophysical Journal, and Monthly Notices of the Royal Astronomical Society the top venues.
Publishing costs are estimated at 17 million USD paid in 2025, or 45 million USD if every paper paid the average fee; authors paid roughly 500–700 USD per citation.
The typical paper has about 10 authors, roughly two-thirds from the first author's country, and most collaboration is bilateral; US and China authors together make up over a third of the field.
Citation density varies sharply by subfield: cosmology papers average 4.83 citations per paper while instrumentation papers average 1.06, even though galaxy papers dominate publication counts.

Where Pith is reading between the lines

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

Repeated annually, the same pipeline would produce the first continuous time series of field-level priorities, making shifts in instrument use, object focus, and collaboration patterns measurable rather than anecdotal.
Because the matching method sees only titles and abstracts and ignores cross-submissions and replacements, the telescope and object counts are best read as lower bounds; full-text or embedding-based matching could recover missed mentions and eliminate false positives like the admitted Apple M1 chip counted as Messier 1.
The collaboration indices could be tested against a null model: randomly reshuffle author-country assignments and see whether the observed local-versus-global distributions differ meaningfully from chance, which would quantify whether the 'local first' pattern is a real signal.
The cost-per-citation estimates assume full use of discounts and ignore institutional agreements; combining this paper's data with actual invoice data would bracket the true financial burden on the community.

Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

Useful descriptive census of 2025 astro-ph, but the telescope ranking is known-wrong by the authors' own LIGO check, and the promised spectral fingerprint is missing.

read the letter

Colleague,

This is a descriptive bibliometric survey, not a physical claim, so judge it on its own terms. The genuinely new material: a compiled census of all 18,660 astro-ph papers on arXiv in 2025, with keyword, subfield, telescope, citation, journal-cost, and collaboration breakdowns. That is useful reference material for students, science-policy people, and anyone wanting a map of the field. The collaboration indices (LCI, LCR, GCI, NGCI) are transparent and used carefully, with sensible caveats about small-number countries like Burkina Faso. The cost estimates — $17M total, ~$2,400 per paper — are clearly framed as lower limits. Those are the strengths.

The soft spots are real, and one of them is load-bearing. The 'high-fidelity census' claim runs on hand-built name lists matched against titles and abstracts, with no quantified error rate. The authors' own LIGO example is the tell: LIGO is absent from the top-10 telescope list, yet searching for 'GW' plus six digits finds 365 mentions, and they conclude LIGO should sit between Fermi and Rubin — then never apply that correction to Figure 1 or Table 3. The telescope ranking is not merely unvalidated; it is known to be wrong in at least one instance. The same pipeline drives the subfield, keyword, object, and exoplanet rankings. They admit the Apple M1/Messier 1 miscount and say random checks found no other errors, but that cannot bound systematic false negatives when papers use event names rather than instrument names.

Other issues: the abstract promises 'a first of its kind Astrophysical Spectral Fingerprint' and the paper never delivers it. The KS test in Section 3.9 is interpreted backwards — p-values of 0 with a nonzero KS statistic indicate a significant difference, not the reverse. Affiliations cover only 57% of papers (the LaTeX-based country fill to 97% is a nice fix). No code, data, or alias lists are released, so the headline rankings cannot be independently checked. All of these are addressable rather than fatal.

The reader's conditional verdict and the stress-test note land correctly. This paper deserves a serious referee because the compiled resource is useful, but it needs a major revision: release the data and match lists, apply LIGO-style checks systematically, fix the KS interpretation, and either deliver or delete the spectral-fingerprint section. I would not desk-reject it; I would send it out with the expectation of heavy revision.

Referee Report

5 major / 5 minor

Summary. The paper presents a year-in-review census of all 18,660 astro-ph arXiv papers submitted in 2025. It compiles counts and rankings of keywords, subfields, telescopes, objects (GW, GRB, FRB, supernovae, pulsars, exoplanets, Messier/NGC), journals, author affiliations, collaboration indices, citation metrics, and publication costs. The authors define several transparent indices (LCI, LCR, GCI, NGCI, AAC/JAC/EAAC/EJAC) and apply them to the collected metadata. The central claim, stated in §2.1, is that the dataset is 'complete, high fidelity,' and the paper presents it as a holistic statistical summary of the field for 2025. The manuscript is candid about some limitations, such as incomplete affiliation coverage (57%) and the use of string matching for object/telescope identification, but several of these limitations are load-bearing for the paper's main deliverable.

Significance. If the census were reliable, it would be a useful community resource: a single quantitative snapshot of what the field studied, with which instruments, from where, and at what cost. The paper's strengths include the transparent definition of collaboration and citation indices, the broad scope of metadata collection, and the honest acknowledgment that the telescope/object matching is not the most robust method. However, the paper's value rests on the accuracy of its rankings, and the manuscript itself provides counterexamples where the string-matching pipeline produces known errors that are not corrected in the reported results. The statistical interpretation also contains a clear error. With corrections, quantified validation, and release of the underlying matching lists and counts, this could be a credible reference census; in its current form, the central 'high-fidelity' claim is not yet established.

major comments (5)

[§3.2, Fig. 1, Table 3] The telescope rankings, a central deliverable, rest on unvalidated string matching. The paper itself demonstrates a systematic false-negative: searching for the GWXXXXXX event format yields 365 mentions, and the text concludes that LIGO 'should indeed be much higher up on the list, somewhere between Fermi and the Vera C Rubin Observatory.' Yet Fig. 1 and Table 3 are never updated to reflect this. The admitted Apple M1 / Messier 1 false positive (§3.2) shows that errors go in both directions. Without released alias lists and quantified false-positive/false-negative rates, the §2.1 claim of a 'complete, high fidelity dataset' is not supported for the object/telescope/subfield/keyword rankings.
[§3.9] The KS test is misinterpreted. The text states: 'A simple KS test ... yields KS statistic values≤0.1 with p-values = 0, showing us that there is no significant difference.' A p-value of 0 rejects the null hypothesis of identical distributions at any conventional significance level; it does not show no difference. This error directly affects the conclusions that subfields and journals write similarly long papers with the same numbers of tables and figures. The test should be reinterpreted or replaced with an appropriate comparison, and the conclusions in §3.8-§3.9 revised accordingly.
[Abstract vs. full text] The abstract advertises 'a first of its kind Astrophysical Spectral Fingerprint showing the distribution of research across the electromagnetic spectrum as well as the distribution of research by redshift.' No such section, figure, or tabulated result appears anywhere in the manuscript. The only redshift-related statistic is the 'Community's Favourite Redshift' and interquartile range in §4. Either the Spectral Fingerprint analysis was intended but omitted, or it should be removed from the abstract. In its current form, a promised headline result is missing.
[§2.1, §3.4] The collaboration and geolocation statistics are based on affiliations available for only 57% of papers, with country/region information extended to 97% using a LaTeX-based method. The paper asserts that the 57% subset is representative, but provides no quantitative evidence (e.g., coverage by month, primary subject, or author count). The ADS affiliations also reflect December 2025 current positions rather than affiliations at the time of submission. Since LCI/LCR/GCI/NGCI, country rankings, and pairwise collaboration counts are central results, the absence of coverage-bias analysis and uncertainty quantification is a load-bearing gap.
[§3.6, Fig. 14] Self-assigned keywords are generated by matching title/abstract words against a list of ~1000 frequent author-assigned keywords, and the paper then presents combined 'with self-assigned keywords' rankings as if these two sources are comparable. The paper itself shows that the lists diverge substantially: 'galaxy evolution' is third in the author-assigned list but disappears when self-assigned keywords are included. This demonstrates that the two measures are not interchangeable, yet no validation is provided for the assumption that word-matching generates keywords equivalent to author-assigned ones. The 'with self-assigned' results should be presented as a separate sensitivity analysis or explicitly validated.

minor comments (5)

[§2.3] In the definition of EAAC, 'the same as the ACC' should read 'the same as the AAC.'
[§2.2] In the LCR example, '60&' should be '60%'.
[Appendix A, Figs. A6-A21] Figures A6 through A21 are all captioned 'Histogram of LCI,' which makes them uninformative as printed. If they are intended to show different indices (LCI, LCR, GCI, NGCI), the captions should be corrected.
[§3.2, Table 3] The text says LIGO is not on the top-10 most-mentioned telescope list, but Table 3 does include LIGO among the telescope citation indices. This is not a contradiction, but the relationship between Fig. 1, Table 3, and the text would be clearer if the table were explicitly described as covering all searched telescopes, not only the top-10 list.
[§3.3] The statement 'we estimate the community spent 17 million USD' is presented without a breakdown of journal-by-journal assumptions or a sensitivity analysis. A short table listing the top journals, their APCs, and the assumed discount rates would improve reproducibility.

Circularity Check

0 steps flagged

No circularity: the paper is a transparent data-processing census; its known LIGO matching failure is a validity issue, not a derivation that reduces to its own inputs.

full rationale

The paper's central claim is to present statistics computed from arXiv metadata and title/abstract string matching. There is no fitted model, no derived quantity that is used to predict the same quantity from which it was fit, and no load-bearing self-citation chain. The collaboration and citation indices are explicitly defined (Section 2.2, 2.3) and computed directly from collected data. The one deliberately generative step — assigning 'self-assigned keywords' to papers lacking author keywords by matching title/abstract words against a frequency list built from author-assigned keywords — is disclosed as a processing choice rather than presented as a prediction; the paper clearly separates analyses with and without these self-assigned keywords. The known LIGO undercount (Section 3.2: LIGO absent from the top-10 list yet 'GWXXXXXX' searches yield 365 mentions, so LIGO 'should indeed be much higher up on the list') is an acknowledged accuracy failure in a pattern-matching pipeline, not a circular derivation: the correction is derived from an independent naming convention, not from the telescope ranking itself. Similarly, the Apple M1 counted as Messier 1 is an admitted false positive that does not make the ranking equivalent to its input. Concerns about unquantified false-positive/false-negative rates, unreleased alias lists, and the small-sample caveats for country-level indices are correctness or reproducibility risks, not circularity. The paper does not invoke any uniqueness theorem, does not cite its own prior work as evidence, and does not rename an existing empirical pattern as a derivation. Under the stated rules, an honest non-finding is appropriate: score 0.

Axiom & Free-Parameter Ledger

6 free parameters · 4 axioms · 1 invented entities

The headline statistics depend on hand-built lists and thresholds (telescopes, subfields, keywords, team-size cutoffs) and on the representativeness of partial affiliation data. These are methodological choices rather than hidden fitted parameters, but they are free in the sense that changing them changes the reported rankings. The only genuinely new postulated artifact is the promised spectral fingerprint, which is not delivered.

free parameters (6)

Self-assigned keyword count per paper = 3
Papers without author keywords receive exactly 3 keywords matched from the top-keyword list; this changes keyword rankings when included (§2.1, §3.6).
Top-keyword list size = ~1000
The list is built from the 68% of papers that already had keywords; the composition of this list determines self-assigned keywords and shifts top-keyword tables (§2.1).
Telescope name list size = 40
Telescope rankings are defined by string matching against 40 hand-picked telescope names; adding or removing names changes counts such as the JWST/GAIA gap (§3.2).
Subfield list size = ~100
Each paper is assigned the first matching subfield from a hand-built list of about 100 areas; the resulting 'Simulations', 'Star Formation' rankings depend on list composition (§3.7).
Large-team author cutoffs = 30 and 20 authors
The paper defines 'large teams' at >30 authors (5.86% of dataset) and also reports >20 authors (10.61%); the choice changes how collaboration statistics are described (§3.4).
Average publication cost per paper = $2,400
The $17M and $45M totals depend on an assumed gold-OA average cost; the authors call it a lower limit, but the underlying APC model is not fully specified (§3.3).

axioms (4)

domain assumption String matching of telescope and object names in titles/abstracts is a valid proxy for what instruments and targets a paper actually uses.
Underpins the telescope, GW/GRB/FRB, pulsar, supernova, exoplanet, Messier and NGC rankings in §3.2; the authors explicitly call it 'not the most robust way'.
domain assumption The 57% affiliation sample is representative of the full 18,660-paper dataset.
Affiliation-based country, collaboration and institution statistics are generalized from partial coverage (§2.1); the extension to 96% geographic coverage relies on less-verified LaTeX parsing.
domain assumption NASA ADS citation counts as of December 2025 are an accurate measure of a 2025 paper's influence.
Citation indices in §2.3 and throughout assume ADS completeness and equal citation windows, even though late-2025 papers have had very little time to accrue citations.
ad hoc to paper Self-assigned keywords generated from title/abstract word matching are comparable to author-assigned keywords.
The paper's own analysis shows rankings change when self-assigned keywords are included (§3.6), so the comparability of the two keyword sets is assumed rather than demonstrated.

invented entities (1)

Astrophysical Spectral Fingerprint no independent evidence
purpose: Abstract claims a first-of-its-kind visualization of research distribution across the electromagnetic spectrum and by redshift.
No section, figure or table named 'spectral fingerprint' appears in the full text; only scattered redshift mentions (e.g., z=0 favorite redshift) are present. It is currently an unsupported advertised artifact.

pith-pipeline@v1.3.0-alltime-deepseek · 22612 in / 11585 out tokens · 117210 ms · 2026-08-03T00:09:54.565533+00:00 · methodology

0 comments

read the original abstract

Astrophysics has experienced an overwhelming increase in research output, as is evident from the year-over-year increase in the number of research papers submitted to the online repository arXiv. As a result, keeping up with progress happening outside our respective sub-fields can be exhausting. While it is impossible to be informed on every single aspect of every sub-field, this paper aims to be the next best thing. We present a summary of statistics for every paper uploaded onto the Astrophysics arXiv over the past year - 2025. We analyse a host of metrics like the most used keywords, subfields and telescopes, the distribution of journals, the most studied astrophysical objects like GW, GRB, FRB events, exoplanets and much more. We also indexed the authors' affiliations to put into context the global distribution of research and collaboration. Combining this data with the citation information of each paper allows us to understand how influential different papers have been on the progress of the field this year. We also present a first of its kind Astrophysical Spectral Fingerprint showing the distribution of research across the electromagnetic spectrum as well as the distribution of research by redshift. Overall, these statistics highlight the general current state of the field, the hot topics people are working on and the different research communities across the globe and how they function. We hope that this is helpful for both students and professionals alike to adapt their current trajectories to better benefit the field.

Figures

Figures reproduced from arXiv: 2602.12303 by Amruth Alfred, Hetansh Shah, Rommulus Francis Lewis.

**Figure 1.** Figure 1: Top 10 Most Mentioned Telescopes in 2025 arXiv papers. The number of papers are represented both as the relative height of the bars and as a colour map for readers with different visual preferences for interpreting data. GAIA is the only telescope with a hatched bar, as it is the only telescope that is not currently operational. For more information refer to Section 3.2. 2.3 Citation Indices From the NASA … view at source ↗

**Figure 2.** Figure 2: Top Primary Subject by First Author Country or Region. First authors with multiple affiliations have each region counted individually. For example, a first author affiliated with China and the US under ‘Astrophysics of Galaxies’ will have one count for the category going to China and one going to the US. All countries or regions in white had no papers this year or were missed by our affiliation extraction … view at source ↗

**Figure 3.** Figure 3: Monthly Distribution of Papers coloured by the arXiv Primary Subject they were submitted under. The plot also shows us that October, September and July were the months with the most number of papers added to the arXiv. Subject Statistics including citation indices are available in [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗

**Figure 4.** Figure 4: Heat-map of Telescope Citation Indices 6 [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗

**Figure 5.** Figure 5: Yearly Track of the Percentage of Open Access Journal Papers. The two bins correspond to the two halves of the year with the dotted line as the mean and shaded regions as the 1𝜎 regions. The drop in the second half is not statistically significant and is due to long journal processing times. would mean a total cost of 45 million USD on publishing. These numbers are similar to those obtained in Coles (2025)… view at source ↗

**Figure 6.** Figure 6: Top 15 Countries or Regions that submitted papers to the arXiv with all authors included. Multiple authors from the same country on the same paper are counted separately [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗

**Figure 7.** Figure 7: Top 15 Countries or Regions that submitted papers to the arXiv counting only first author papers. First authors with multiple affiliations from the same or different country are counted separately. unique countries or regions involved in a paper other than the first author’s The median LCI taken over the entire dataset is 4.00, while the average is 6.48, skewed most likely by the papers from large collabor… view at source ↗

**Figure 8.** Figure 8: Heat Map of Top 5 Country and Region Pair-wise Collaborations • Albania: 477.00 • Italy: 281.79 • Taiwan: 271.91 • Belgium: 262.37 • Netherlands: 247.68 • France: 206.34 • India: 194.14 The top 10 most internationally diverse collaborative countries and regions (highest NGCI) are: • Bosnia and Herzegovina: 57.00 • Albania: 57.00 • Philippines: 15.29 • Romania: 13.69 • Lebanon: 13.68 • Malta: 13.45 • Burkin… view at source ↗

**Figure 9.** Figure 9: Global Distribution of LCI [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗

**Figure 10.** Figure 10: Global Distribution of LCR [PITH_FULL_IMAGE:figures/full_fig_p012_10.png] view at source ↗

**Figure 11.** Figure 11: Global Distribution of GCI maps with the four indices in Figures 9, 10, 11, 12. One plot we thought would be interesting to show is the global collaboration network. To do so, we create a graph with each node as one of the top 20 first author countries or regions. The nodes are interconnected by the authors that are affiliated with regions other than the first author’s region [PITH_FULL_IMAGE:figures/ful… view at source ↗

**Figure 13.** Figure 13: Global Network of Collaboration (Top 20 First Author Countries or Regions) words all have collaborative indices within one standard deviation of the mean of the whole sample and hence show no significant difference. This conclusion remains valid irrespective of if we include self-assigned keywords (for more details, refer to sub-section 3.6) or not. Even when considering subfields, another metric we talk… view at source ↗

**Figure 14.** Figure 14: Most Common Keywords for 2025 15 [PITH_FULL_IMAGE:figures/full_fig_p015_14.png] view at source ↗

**Figure 15.** Figure 15: Top 25 Most Commonly assigned Subfields Subfield AAC EAAC JAC EJAC Scalar-Tensor Gravity 11.5 11.5 23.0 23 Dark Energy 8.59 7.25 9.63 8.07 Cosmic Microwave Background 7.89 6.70 15.57 13.29 Cosmic Reionization 6.82 4.64 4.0 2.25 Inflation 5.44 4.85 8.67 7.70 Early Universe 4.61 3.25 6.61 4.97 Epoch of Reionization 4.11 2.67 7.07 4.48 Hubble Tension 4.05 3.02 4.44 2.33 Black Holes 3.83 2.82 4.17 3.06 Galaxy… view at source ↗

**Figure 16.** Figure 16: Monthly Track of the Percentage of Journal Published Papers. The two bins correspond to the two halves of the year with the dotted line as the mean and shaded regions as the 1𝜎 regions. The drop in the second half is not statistically significant and is due to long journal processing times. where authors often mention the publication or submission status of their paper. For the remaining articles that had… view at source ↗

**Figure 18.** Figure 18: Pie Chart of the Top Journals into which arXiv articles were published Japan’, ‘Science China Physics, Mechanics & Astronomy’, ‘Revista Mexicana de Astronomía y Astrofísica’, etc. The list has been made as inclusive as possible [PITH_FULL_IMAGE:figures/full_fig_p017_18.png] view at source ↗

**Figure 19.** Figure 19: Distribution of the Number of Paper Pages [PITH_FULL_IMAGE:figures/full_fig_p018_19.png] view at source ↗

**Figure 20.** Figure 20: Distribution of the Number of Paper Tables length of the abstract at 211 words per paper. Across primary subjects, the word count for titles and abstracts is within 1𝜎 of the mean, demonstrating that there is no significant difference. We can also analyse if the papers associated with different telescopes tend to have longer or shorter titles or abstracts. While both the length of the title and abstract f… view at source ↗

**Figure 23.** Figure 23: Citations against Abstract Length conducting the analysis for this paper that could not fit in anywhere else. • Longest Paper: Statistical Machine Learning for Astronomy – A Textbook Pages: 677 • Longest Paper (excluding books): The TESS Grand Unified Hot Jupiter Survey. III. Thirty More Giant Planets Pages: 96 • Paper with the most Figures: Thermodynamic Origin of the Tully-Fisher Relation in Dark Matter… view at source ↗

**Figure 22.** Figure 22: Citations against Title Length weak positive monotonic relation between title and abstract length and the number of citations, allowing us to conclude that title and abstract length are not major determiners of the number of citations. Changing the citation index does not change the conclusion of this result. 4 HONOURS AND MEDALS In honour of the Spotify Wrapped (the inspiration for this paper) awarding l… view at source ↗

discussion (0)

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

Calibration database design for the wide-field X-ray telescope on board the Einstein Probe
astro-ph.IM 2026-07 accept novelty 5.0

The WXT CALDB is a HEASARC/OGIP-compliant database of per-CMOS calibration files — bias, gain, bad pixels, effective area, response matrices, PSF and vignetting — with in-orbit updates validated against the Crab and Cas A.

Reference graph

Works this paper leans on

1 extracted references · cited by 1 Pith paper

[1]

We also have the table of the top keyword and top sub-field for every country or region in our dataset at the very end

Coles P., 2025, Like a million pounds: Published by The Open Journal of Astrophysics,https://astro.theoj.org/post/ 3602-like-a-million-pounds 20 Figure A1.Histogram of LCI Figure A2.Histogram of LCR Figure A3.Histogram of GCI APPENDIX A: ADDITIONAL PLOTS Here we present some plots that we found interesting and might be interesting to some of the readers. ...

2025

[1] [1]

We also have the table of the top keyword and top sub-field for every country or region in our dataset at the very end

Coles P., 2025, Like a million pounds: Published by The Open Journal of Astrophysics,https://astro.theoj.org/post/ 3602-like-a-million-pounds 20 Figure A1.Histogram of LCI Figure A2.Histogram of LCR Figure A3.Histogram of GCI APPENDIX A: ADDITIONAL PLOTS Here we present some plots that we found interesting and might be interesting to some of the readers. ...

2025