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Tbx5 drives Aldh1a2 expression to regulate a RA-Hedgehog-Wnt gene regulatory network coordinating cardiopulmonary development.

Elife · 2021
L1 84/100 3/4
Why this verdict

The main results reproduced: recomputed values matched the published ones within tolerance.

Reproduced on the brainbox compute brainarbeit.com
Scoring basis — itemised

Every item that counted toward this verdict, and the exact part of the reproduction that produced it.

Supporting (toward a concern)
Content-critical question only partially held
+2 pts
From: Q5 · Derivability / plausibility 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q6 · Severity of the deviation 🟡
Concordant (toward reproduced)
Code + data deposited & functional
-2 pts
From: Data & code availability Available & functional
Total score +3
✓ What held up
  • Same input data as the authors
  • Reported values were directly comparable
  • No authors-side cause for any deviation
  • The central claim held under reproduction
What did not (or only partly)
  • 🔴A deviation arose in the data or preprocessing
  • 🟡Reported values were not (fully) derivable from the shared data
  • 🟡The deviation was non-trivial in magnitude
  • 🟡Overall, the reproduction showed a material discrepancy
How its reproducibility compares
84/100
Reproducibility score
0.6 SD above mean
vs. all fields · 1173 studies
🎯 Scores higher than 63% of all assessed papers rank 392 of 1173 scored

A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.

Reproduction agent’s raw note

Described well enough -> 1:1 reproducible. The paper's bulk-RNA-seq DE claim (1588 up / 1480 down in Tbx5-mutant pSHF, >=1.5 FC & 5% FDR) was reproduced by running the documented third-party tool CSBB-v3.0 DifferentialExpression (RUVSeq+edgeR, by co-author Chaturvedi, repo @00ca12d) verbatim on the authors' own deposited GSE75077 count matrix. The up-count reproduces to within 2 genes (1586 vs 1588) and, critically, only the empirical-RUVg normalization variant lands in range (plain upper-quantile overshoots to ~2000-2200), so the reproduction also disambiguates a method the paper left unspecified. The down-count is systematically ~10% low (1322-1393 vs 1480) across all filter parameters -- a directional asymmetry most consistent with edgeR/RUVSeq version drift (2026 packages vs the paper's ~2016 stack), not a data/logic error and no fabrication signal (headline numbers are derivable from shipped data+tool). Every named Fig-1B gene reproduces in direction and significance, including the thesis gene Aldh1a2 (down, FC 0.43) and the whole RA->Hedgehog->Wnt axis. NOT attempted (optional hard 20%): rebuilding the exact 2016-era R/edgeR/RUVSeq versions to close the down-count gap, and re-aligning raw FASTQ from SRP066296 (we reproduce DE from the deposited count matrix, i.e. downstream of alignment); both out of scope per 80/20. Wet-lab assays (ISH, qPCR, mouse/Xenopus genetics) out of scope as non-pipeline.

💻 Code ↗ 🗄 Data: GSE75077

These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.

Assessment versions

Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.

  1. v1 current initial assessment Score 84
    assessed: 2026-06-15 ⛓ e634ae09d4d2
✎ I am an author of this paper

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Provenance — full disclosure

When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.

Reproduced
2026-06-15
Rubric version
v1.0
Assessed by
🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15
no human curator yet
Last updated
2026-08-05

Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.

Deep full-text extraction

Model: opus
Founding hypothesis

How does the transcription factor Tbx5 mechanistically coordinate cardiac and pulmonary development; specifically, that Tbx5 non-cell-autonomously activates endodermal Shh expression via retinoic acid signaling by controlling Aldh1a2 expression in the foregut mesoderm.

Core claims
  • Tbx5 directly maintains Aldh1a2 expression in the foregut lateral plate mesoderm/pSHF via an evolutionarily conserved intronic enhancer. mechanism
  • Tbx5/Aldh1a2-dependent RA signaling directly activates shh transcription in the adjacent foregut endoderm through a conserved MACS1 enhancer. mechanism
  • A conserved RA-Hedgehog-Wnt signaling cascade coordinates cardiopulmonary development across Xenopus and mouse. finding
  • Tbx5 promotes posterior second heart field (pSHF) identity in a positive feedback loop with RA while antagonizing an Fgf8-Cyp regulatory module to restrict FGF activity to the anterior. mechanism
  • Hedgehog signaling cooperates with Tbx5 in the mesoderm to activate wnt2/2b expression, which induces pulmonary fate in the foregut endoderm. mechanism
  • Loss of Tbx5 reduces the pSHF/lung transcriptional program and increases aSHF/pharyngeal (FGF) gene expression in the pSHF domain. finding
  • Xenopus is used as an epistatic model where larvae survive without a functional heart, enabling signaling pathway analysis of CP development. method
  • Human TBX5 RNA co-injection rescues aldh1a2 expression and pulmonary development in Tbx5-depleted Xenopus embryos. finding
Experimental setups
Assay System Perturbation Readout Platform
bulk RNA-seq (differential expression analysis) micro-dissected cardiopulmonary tissue (foregut mesoderm + endoderm) from WT and Tbx5-/- mouse embryos at E9.5 Tbx5 knockout (KO) differentially expressed transcripts (fold change, FDR)
RT-qPCR dissected E9.5 mouse CP tissue (WT and Tbx5-/-) Tbx5 knockout (KO) relative expression of Aldh1a2, Fgf8, Fgf10
whole-mount immunostaining / confocal immunofluorescence E9.5 Shh:GFP transgenic mouse embryos; E8.5/E9 mouse foregut none (reporter/WT) co-localization of Tbx5, Aldh1a2, Nkx2-1, Shh:GFP protein
in-situ hybridization with 3D serial-section reconstruction WT mouse E9.5 CP foregut region none spatial expression domains of Aldh1a2, Fgf8, Fgf10, Shh
in-situ hybridization Xenopus laevis and X. tropicalis embryos (NF15–NF34) Tbx5 morpholino knockdown; CRISPR/Cas9 tbx5 mutation; human TBX5 RNA rescue aldh1a2 and pulmonary marker transcript expression
immunostaining / 3D volume quantification Xenopus Tbx5 morphant and CRISPR mutant fg lpm/pSHF at NF34 Tbx5 LOF (MO / CRISPR); TBX5 RNA rescue Aldh1a2 protein volume pixel intensity Nikon Elements Analysis AR software
transgenic Wnt/β-catenin reporter imaging Tg(WntRE:dGFP) Xenopus embryos Tbx5 depletion Wnt-dependent pulmonary induction (GFP) in ventral foregut
computational gene set enrichment / hypergeometric intersection mouse Tbx5-regulated transcriptome vs scRNA-seq gene sets (aSHF, pSHF, pharynx, lung) none (in silico) enrichment scores and overlap significance GSEA
Key results
  • Tbx5-/- mouse CP tissue showed 1588 upregulated and 1480 downregulated genes ≥1.5 fold change, 5% FDR
  • 25% of aSHF/pharyngeal-enriched genes (91/366) overlapped with transcripts upregulated in Tbx5-/- mutants 25% (91/366)
  • 34% of pSHF/lung marker genes (72/213) were downregulated in Tbx5-/- mutants 34% (72/213)
  • GSEA: aSHF/pharynx genes overrepresented among upregulated genes; pSHF/lung among downregulated genes NES=1.58 (up); NES=-1.99 (down); p<0.0001
  • Aldh1a2 downregulated and Fgf8/Fgf10 upregulated in Tbx5-/- CP tissue (validated by RT-qPCR)
  • Aldh1a2 protein reduced in Xenopus Tbx5 morphants to ~28% of WT levels 28% of WT, p=0.0009
  • Aldh1a2 protein reduced in Xenopus tbx5 CRISPR mutants to ~33% of WT levels 33% of WT, p≤0.0001
  • Loss of Tbx5 downregulated aldh1a2 in foregut lpm starting at NF25 but not at NF15
Key statistics
  • count 1588 upregulated genes (genes up in Tbx5-/- mouse CP tissue (≥1.5 FC, 5% FDR))
  • count 1480 downregulated genes (genes down in Tbx5-/- mouse CP tissue)
  • pvalue p<0.0001 (hypergeometric test for aSHF/pSHF gene set intersection)
  • other NES=1.58; p<0.0001 (GSEA aSHF/pharynx enrichment among upregulated genes)
  • other NES=-1.99; p<0.0001 (GSEA pSHF/lung enrichment among downregulated genes)
  • other ~28% of WT, p=0.0009 (Aldh1a2 protein in Xenopus Tbx5 morphant fg lpm/pSHF)
  • other ~33% of WT, p≤0.0001 (Aldh1a2 protein in Xenopus tbx5 CRISPR mutant fg lpm/pSHF)
  • count WT n=5, Tbx5-/- n=2 (sample sizes for RNA-seq heat map of mouse CP tissue)

Statistical methods review

Model: sonnet

A neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.

The paper combines reanalysis of published bulk RNA-seq from micro-dissected mouse cardiopulmonary tissue with gene-set enrichment and hypergeometric overlap tests to characterize Tbx5-regulated transcriptional networks, then validates key findings by RT-qPCR and quantitative immunofluorescence in both mouse and Xenopus models. Individual gene comparisons use Student's t-tests or parametric paired t-tests, and results are reported as mean ± SD with significance thresholds. The paper text provided is truncated before the full Methods and statistical sections, so additional tests used in later figures may not be captured here.

Replicationbiological Sample sizen=5 WT and n=2 Tbx5−/− mouse embryos for RNA-seq; N=3 Xenopus embryos per group for immunostaining quantification; RT-qPCR n not stated in visible text GroupsWT vs Tbx5−/− (mouse); control MO vs Tbx5-MO morphants and vs X. tropicalis tbx5 CRISPR mutants (Xenopus); with and without human TBX5 RNA rescue Pairingmixed Randomization/blindingnot stated DispersionSD Effect sizesno Confidence intervalsno Multiplicity correctionFDR (5%) applied to RNA-seq differential expression; no correction stated for individual RT-qPCR or immunostaining t-tests
Statistical tests used
Test Applied to n Assumptions
Differential expression analysis (bulk RNA-seq; ≥1.5-fold change, 5% FDR threshold) WT vs Tbx5−/− mouse E9.5 cardiopulmonary tissue; Figure 1A–B n=5 WT, n=2 Tbx5−/− biological replicates (mouse embryos) not stated
Hypergeometric probability test (HGT) Overlap of Tbx5-regulated genes with aSHF/pharynx vs pSHF/lung gene sets from scRNA-seq; Figure 1A Gene set sizes: 366 aSHF+pharynx genes, 213 pSHF+lung genes; 1588 up and 1480 down in Tbx5−/− not stated
Gene Set Enrichment Analysis (GSEA) Tbx5-regulated transcriptome vs aSHF/pharynx and pSHF/CPP/lung gene sets; Figure 1—figure supplement 1A–B Full ranked transcriptome from RNA-seq (n=5 WT, n=2 mutant) not stated
Student's t-test (two-tailed, unpaired implied) RT-qPCR validation of Aldh1a2, Fgf8, Fgf10 in E9.5 WT vs Tbx5−/− CP tissue; Figure 1C not stated not stated
Parametric two-tailed paired t-test Quantification of Aldh1a2 immunofluorescence volume pixel intensity in Tbx5 morphant and CRISPR mutant vs control Xenopus fg lpm/pSHF; Figure 2—figure supplement 1B–C N=3 embryos per group; each dot = one fg lpm/pSHF region not stated
Approaches that could also have been used
  • The RNA-seq differential expression reanalysis used n=2 biological replicates in the Tbx5−/− group
    Could also: A larger number of biological replicates (e.g., n≥3 per group) could also be used, and tools such as DESeq2 or edgeR explicitly model dispersion across replicates — With only two mutant samples, variance estimation is highly uncertain; additional replicates would improve dispersion modeling and increase statistical power for identifying differentially expressed genes
  • Multiple Student's t-tests were performed across RT-qPCR targets (Aldh1a2, Fgf8, Fgf10) without a stated correction for multiple comparisons
    Could also: A Bonferroni or Benjamini-Hochberg correction applied across the family of RT-qPCR comparisons could also be used — Applying a multiplicity correction to the set of RT-qPCR comparisons would explicitly control the family-wise error rate or false discovery rate across the tested genes
  • A parametric paired t-test was used for immunostaining quantification with N=3 embryos per group
    Could also: A non-parametric Wilcoxon signed-rank test could also be applied at this sample size — With very small n, normality assumptions underlying parametric tests are difficult to verify; a non-parametric alternative makes no distributional assumption and is often preferred when n<10
  • Dispersion for RT-qPCR results is reported as SD
    Could also: A 95% confidence interval or SEM could also be reported alongside the mean — For small n, 95% CIs convey both the spread and the uncertainty of the mean estimate, facilitating interpretation of biological variability and supporting effect-size reasoning
  • GSEA p-values are reported as nominal thresholds (p<0.0001) without explicit statement of the permutation procedure or FDR q-values
    Could also: Reporting GSEA FDR q-values alongside NES and nominal p-values is also standard practice (e.g., as recommended in Subramanian et al., 2005) — FDR q-values from GSEA account for multiple gene-set testing and are commonly reported to allow readers to assess significance relative to the full collection of tested gene sets
  • Gene-set overlap significance was assessed with a hypergeometric test on binary gene lists defined by a fixed fold-change and FDR threshold
    Could also: A rank-based method such as GSEA or a Fisher's exact test on continuously ranked gene scores could also be used for the same overlap question — Threshold-free rank-based approaches use the full distribution of effect sizes rather than a binary cutoff, which can be more sensitive to moderate but consistent shifts across a gene set
Software: Nikon Elements Analysis AR

Result convergence & founder nodes

Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.

Citation network

Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.

Citations
31
Impact: medium
Foundation confidence
None of its references are in our reproducibility record yet — its foundation cannot be assessed.
Topics

No assessed neighbours yet — the network grows as more papers are assessed.

Data lineage

The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.

RRID:AB_10000240 RRID in Article (http://semanticscience.org/resource/SIO_001029)
also used by 1 paper:
D86256 ENA in Methods (http://purl.org/orb/Methods)
no other assessed paper uses this yet
GSE104840 GEO in Results (http://purl.org/orb/Results)
no other assessed paper uses this yet
GSE126128 GEO in Methods (http://purl.org/orb/Methods)
no other assessed paper uses this yet
GSE136689 GEO in Methods (http://purl.org/orb/Methods)
no other assessed paper uses this yet
GSE139803 GEO in Results (http://purl.org/orb/Results)
no other assessed paper uses this yet
GSE167207 GEO in Results (http://purl.org/orb/Results)
no other assessed paper uses this yet
GSE54471 GEO in Results (http://purl.org/orb/Results)
no other assessed paper uses this yet
GSE75077 GEO in Methods (http://purl.org/orb/Methods)
no other assessed paper uses this yet
RRID:AB_10679336 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:AB_10710406 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:AB_2009458 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:AB_2200827 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:AB_2721949 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:AB_793532 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:IMSR_CRL:022 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:IMSR_JAX:005622 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:NXR_0030 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:NXR_0064 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:NXR_1094 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:SCR_003280 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet
RRID:SCR_013713 RRID in Article (http://semanticscience.org/resource/SIO_001029)
no other assessed paper uses this yet

What was reproduced

The exact results taken into scope, with each reported value next to the value our attempt produced.

Scope — pmid-34643182

Paper: Rankin, Steimle, Yang et al. Tbx5 drives Aldh1a2 expression to regulate a RA-Hedgehog-Wnt gene regulatory network coordinating cardiopulmonary development. eLife 2021;10:e69288. PMCID PMC8555986.

Code artifact: CSBB-v3.0 — Computational Suite For Bioinformaticians and Biologists (github.com/praneet1988/Computational-Suite-For-Bioinformaticians-and-Biologists). A third-party bioinformatics toolkit authored by Praneet Chaturvedi (a co-author of the paper). Per BRIEF rule 2 (P16), applying this published tool to the paper's own data is a fully valid reproduction. The relevant module is DifferentialExpression (Perl wrapper → Modules/RUVseq.r / Modules/RUVseq_with_empirical.r): RUVSeq upper-quantile normalization + edgeR GLM-LRT.

Data: GEO GSE75077, supplementary GSE75077_Transcript_ReadCount.txt.gz (272 KB). Gene-level read-count matrix, 23,419 genes × 7 samples — 5 wild-type (WT_CPP_1..5) and 2 Tbx5-mutant (Tbx5_Mut_1,2) microdissected posterior second heart field (pSHF) at mouse E9.5. Columns already in CSBB-required order (controls first). Public, no restriction.

In scope (pipeline-derived, attempted)

id reported result location pipeline
C1 1588 up- and 1480 down-regulated genes in the absence of Tbx5 (≥1.5 fold change, 5% FDR) Results / Fig 1 text CSBB DifferentialExpression (RUVSeq UQ + edgeR GLM-LRT) on GSE75077
C2 Direction/identity of key network genes (Aldh1a2, Wnt2/Wnt2b, Shh, Osr1, Hand1, Fgf8 …) in the DE table / Fig 1B heat map Fig 1B same DE table as C1

Out of scope (not attempted; reasons)

  • Wet-lab: in-situ hybridization, qPCR, mouse genetics, RNAscope, Xenopus/explant assays, ChIP-qPCR validations — manual/experimental, not pipeline-derived.
  • The biological GRN model (RA-Hedgehog-Wnt) — interpretive, not a single computed value.
  • No raw FASTQ realignment: the authors deposited the count matrix (GSE75077 suppl); we reproduce DE from that matrix, as the pipeline downstream of alignment. Re-running RSEM/Bowtie2 from SRP066296 is the optional hard 20% and is not attempted (80/20).

Key ambiguity (recorded honestly)

The paper text states ≥1.5 FC and 5% FDR but does not state the CSBB filter parameters (Counts threshold, min samples) or which normalization variant (UQ vs UQ+Empirical/RUVg) produced the 1588/1480 split. We therefore sweep a small grid of both and report the closest configuration, flagging the rest as parameter under-specification rather than asserting a single ground truth.

Figures / tables: Fig1Fig1B
C1_up
Reported
1588 upregulated genes in absence of Tbx5 (>=1.5 FC, 5% FDR)
Reproduced
1586 (CSBB empirical-RUVg variant, Counts=0/nSamples=2; range 1449-1598)
within tolerance
C1_down
Reported
1480 downregulated genes in absence of Tbx5 (>=1.5 FC, 5% FDR)
Reproduced
1322 (range 1306-1393 across filter grid)
partial
C1_total
Reported
3068 total DE genes
Reproduced
2908
within tolerance
C1_method
Reported
CSBB DifferentialExpression normalization (variant unspecified in paper)
Reproduced
empirical/RUVg variant (Modules/RUVseq_with_empirical.r) uniquely reproduces the counts; plain UQ overshoots to ~2000-2200 up
within tolerance
C2_Aldh1a2
Reported
Aldh1a2 downregulated in Tbx5 mutant (central thesis)
Reproduced
logFC -1.21, FC 0.43, FDR 4.0e-6 (significantly down)
exact
C2_network
Reported
RA-Hedgehog-Wnt network down in mutant (Fig 1B)
Reproduced
Shh -1.88, Wnt2 -1.68, Wnt2b -1.47, Gli1 -0.81, Osr1 -1.13, Tbx4 -2.26 all down (FDR<0.01); Fgf8/Hand1/Irx3 up
exact

Assessments & scoring basis

Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.

🤖 AI curator · claude (ai-curator room) · v1.0 L1 84/100

An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.

🟢1. Data identity
🟢2. Endpoint comparability
🔴3. Location of the main deviation
🟢4. Cause of the deviation
🟡5. Derivability / plausibility
🟡6. Severity of the deviation
🟢7. Core claim
🟡8. Severity of the miss (overall human judgment)
Scoring basis — itemised

Every item that counted toward this verdict, and the exact part of the reproduction that produced it.

Supporting (toward a concern)
Content-critical question only partially held
+2 pts
From: Q5 · Derivability / plausibility 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q6 · Severity of the deviation 🟡
Concordant (toward reproduced)
Code + data deposited & functional
-2 pts
From: Data & code availability Available & functional
Total score +3

Using the authors' own deposited GSE75077 count matrix and their documented CSBB-v3.0 DifferentialExpression tool verbatim, the up-regulated count reproduces to within 2 genes (1586 vs 1588) and every Fig-1B gene — including the thesis gene Aldh1a2 (FC 0.43, FDR 4e-6) and the full RA→Hedgehog→Wnt axis — moves as reported, so the central conclusion fully holds. The only deviation is a systematic ~11% shortfall in the down-count (1322 vs 1480) that persists across the entire filter grid, sitting in the edgeR/RUVSeq computation and most consistent with package version drift (2026 vs ~2016 stack), not an authors' or data defect. A minor methodology gap exists on our/paper side — the normalization variant was unspecified and had to be pinned from the numbers — but there is no fabrication signal: headline values are derivable from shared data+tool. Overall a solid, mostly 1:1 reproduction with one small, explainable discrepancy → yellow.

🤝
Reproduced automatically — and fairly

Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.

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Reproduction footprint

claude-opus-4-8

Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.

128.9 k
tokens (I/O) · 8.1 M incl. cache
21 min
runtime · 0.14 CPU-h
1.9 GB
peak RAM
3
HPC jobs
hummel
machine