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Phylogenetic analysis of higher-level relationships within Hydroidolina (Cnidaria: Hydrozoa) using mitochondrial genome data and insight into their mitochondria

PeerJ · 2015
L1 68/100 3/4
⚑ Flagged for review — a reproduced result did not match the reported value

Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.

Why this verdict

The main results reproduced, with only marginal, non-material deviations.

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: Q7 · Core claim 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q4 · Cause of the deviation 🟡
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 +6
✓ What held up
  • Same input data as the authors
  • Reported values were directly comparable
What did not (or only partly)
  • 🔴A deviation arose in the data or preprocessing
  • 🟡A deviation was attributed to the published material
  • 🟡Reported values were not (fully) derivable from the shared data
  • 🟡The deviation was non-trivial in magnitude
  • 🟡The central claim did not (fully) hold under reproduction
  • 🟡Overall, the reproduction showed a material discrepancy
How its reproducibility compares
68/100
Reproducibility score
0.3 SD below mean
vs. all fields · 1173 studies
🎯 Scores higher than 32% of all assessed papers rank 765 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 to reproduce the headline result 1:1 via a third-party-tool route (P16): the GitHub 'code' link (bastodian/shed) is the author's generic scratch repo, NOT this paper's pipeline, but the paper deposited its actual analysis inputs as Supplemental FASTA alignments. We re-ran the paper's described tool (RAxML v8.2.12, ML, GTR+GAMMA, 100 rapid bootstraps) on the paper's own published allNT alignment (Dataset S2) on «our HPC». RESULT = mostly 1:1: the primary matrix dimensions match exactly (allNT 12018, rRNA 2154; embedded NT 12018-2154=9864 also exact), and 3 of 4 tested headline clades reproduce with ML bootstrap 100 matching Table 3 (Siphonophora monophyletic & earliest-diverging; Leptothecata; Trachylina outgroup). One clear DIFFERENCE: Aplanulata is NOT recovered as monophyletic in our single-partition GTR+G ML tree (Boreohydra+Plotocnide sit on a long branch away from Euphysa+Hydra) - a plausible long-branch / model-partitioning sensitivity, since the paper applied GTR to the concatenated set and also ran Bayesian MrBayes. NOT ATTEMPTED (optional 20%): per-gene/codon partitioned model, the MrBayes Bayesian analysis (10M gen x2x4), de-novo mitogenome assembly from SRR923510 (proprietary Geneious v7 + manual MITObim/MIRA), and individual resolution of ~20 accession-only outgroup/congeneric tips. Auditable supplement discrepancy flagged (no fabrication indicated): standalone AA(3144)/NT(10686) datasets are larger than the Methods-quoted final 2902/9864, while the concatenation matches exactly. AA/NT/rRNA ML cross-check runs were submitted in the same job but not awaited for grading.

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

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  1. v1 current initial assessment Score 68
    assessed: 2026-06-16 ⛓ 484a408db150
✎ I am an author of this paper

Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.

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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
2026-06-16
Rubric version
v1.0
Assessed by
🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16
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

Can nearly-complete mitochondrial genome data resolve the unsettled higher-level (order/suborder) phylogenetic relationships within Hydroidolina, the most speciose hydrozoan subclass, and clarify the mechanism of mitochondrial gene expression in medusozoans?

Core claims
  • Phylogenetic analyses of full mitochondrial gene sets recover siphonophores as the first diverging clade within Hydroidolina, a well-supported Leptothecata–Filifera III–IV clade, and a second clade of Aplanulata–Capitata s.s.–Filifera I–II. finding
  • A novel mitochondrial genome organization is described in Hydroidolina while otherwise confirming prior inference of mtDNA evolution in Hydrozoa. finding
  • RNA-seq data support a proposed mechanism for the expression of mitochondrial mRNA in Hydroidolina that can be extrapolated to other medusozoan taxa. mechanism
  • A relatively inexpensive, accessible multiplexing strategy was developed to sequence long-range PCR amplicons, adaptable to most high-throughput sequencing platforms. method
  • Twenty-six novel, nearly-complete hydroidolinan hydrozoan mitochondrial genomes were generated as a resource. resource
  • Filifera was never recovered as monophyletic, consistent with prior analyses, and Anthoathecata monophyly remains unsupported. finding
Experimental setups
Assay System Perturbation Readout Platform
Long-range PCR amplification and high-throughput sequencing of nearly-complete mtDNA 16 hydrozoan species (Hydroidolina and Trachylina) none nearly-complete mitochondrial genome sequence Illumina HiSeq2000 (100 bp single-end) / Ion Torrent PGM (316 v.1 chip, 200 bp single-end); Ranger Taq (Bioline); Q800R sonicator
RNA-seq mitochondrial genome assembly / transcription inference Nanomia bijuga, Physalia physalis, Craspedacusta sowerbyi, Ectopleura larynx, Podocoryna carnea, Hydractinia polyclina, Hydractinia symbiolongicarpus none mitochondrial mRNA expression mechanism and mtDNA coding regions
DNA-seq library probing for mtDNA assembly Liriope tetraphylla and Cladonema pacificum none mitochondrial genome sequence
Sequence assembly and annotation hydrozoan mitochondrial genomes none protein-coding, tRNA, and rRNA gene identification/annotation Geneious v.7, MITObim v.1.7, MIRA v.4, Bowtie v.2, tRNAscan-SE, ARWEN, BLAST
Multiple sequence alignment and phylogenetic inference (ML and Bayesian) concatenated AA, NT, rRNA, allNT alignments of hydrozoans plus outgroups none phylogenetic tree topology and node support MAFFT v.7, PAL2NAL, Gblocks, RAxML v.8, MrBayes v.3.2.2, jModelTest v.2.1.4, ProtTest v.3
Topology/hypothesis testing (approximately unbiased AU test) constrained hydroidolinan tree topologies none per-site likelihoods comparing competing phylogenetic hypotheses Consel, PhyML v.3.1
Key results
  • Siphonophores recovered as the first diverging clade within Hydroidolina
  • Well-supported clade comprising Leptothecata and Filifera III–IV
  • Second clade comprising Aplanulata, Capitata s.s., and Filifera I–II
  • Twenty-six novel nearly-complete mitochondrial genomes obtained across hydrozoan orders 26 genomes
  • Filifera never recovered as a monophyletic group
Key statistics
  • count 2,902 positions (2,501 informative sites) (AA concatenated alignment)
  • count 9,864 positions (8,850 informative sites) (NT concatenated alignment)
  • count 2,154 positions (1,664 informative sites) (rRNA concatenated alignment)
  • count 12,018 positions (10,773 informative sites) (allNT concatenated alignment)
  • count 26 (novel nearly-complete mitochondrial genomes sequenced)
  • count three species of Trachylina and twenty-three of Hydroidolina (taxon sampling across hydrozoan subclasses)
  • count nineteen non-hydrozoans used as outgroup taxa (outgroup sampling)
  • count 188 non-bilaterian animal mtDNAs sequenced, 124 cnidarians (background on available mtDNA data)

Statistical methods review

Model: opus

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

This is a phylogenetic (phylomitogenomic) study rather than an experiment with replicate-based hypothesis testing. The authors assembled near-complete mitochondrial genomes from 26 hydrozoan species, built concatenated amino-acid, nucleotide and rRNA alignments, selected substitution models (ProtTest/jModelTest), and inferred trees under Maximum Likelihood (RAxML) and Bayesian (MrBayes) frameworks. Competing traditional hypotheses of relationships were evaluated with approximately unbiased (AU) topology tests in Consel using per-site likelihoods from constrained ML searches in PhyML, and compositional bias/saturation were probed with PCA and DAMBE5.

Replicationbiological Sample size26 newly sequenced hydroidolinan species selected to cover all currently recognized hydroidolinan clades; alignment sizes and informative-site counts reported (e.g., 2,501 informative AA sites, 10,773 informative allNT sites) Groupsorder/suborder-level hydroidolinan clades and outgroups; competing topological hypotheses Pairingna Randomization/blindingna Dispersionna Multiplicity correctionnot stated
Statistical tests used
Test Applied to n Assumptions
Maximum Likelihood phylogenetic inference (RAxML v.8; LG model for amino acids, GTR for nucleotides/amino acids) AA, NT, rRNA and allNT concatenated alignments 26 hydroidolinan species plus publicly available medusozoan mitogenomes and 19 non-hydrozoan outgroups; alignment lengths 2,902 AA / 9,864 NT / 2,154 rRNA / 12,018 allNT positions stated
Bayesian phylogenetic inference (MrBayes v.3.2.2; GTR model; two runs of 4 chains, 10,000,000 generations, sampled every 100 trees, burn-in fraction 0.25) AA, NT, rRNA and allNT concatenated alignments same alignments as ML stated
Approximately Unbiased (AU) topology test (Consel) three sets of traditional hypotheses of hydroidolinan relationships, using per-site likelihoods from constrained ML searches in PhyML v.3.1 na
Substitution-model selection (jModelTest v.2.1.4 for nucleotides; ProtTest v.3 for amino acids) nucleotide and amino-acid alignments na
Saturation analysis (DAMBE5) nucleotide alignments (NT, rRNA, allNT) na
Principal Component Analysis (princomp in R) of amino-acid and nucleotide composition compositional-bias assessment of alignments, visualized on first two principal components na
Approaches that could also have been used
  • Branch/clade support is described primarily through the ML and Bayesian frameworks (Bayesian posterior probabilities from MrBayes).
    Could also: Reporting nonparametric bootstrap proportions (or the rapid-bootstrap/SH-aLRT options available in RAxML/PhyML) alongside posterior probabilities. — Bootstrap and posterior support measure confidence in complementary ways, and presenting both is a common convention that gives readers two independent views of node reliability.
  • Phylogenies were inferred using a single substitution model applied across each whole concatenated alignment (GTR/LG selected by jModelTest/ProtTest).
    Could also: Partitioned models (e.g., by gene or codon position) or mixture/site-heterogeneous models such as CAT-GTR in PhyloBayes. — Partitioned or site-heterogeneous models can accommodate rate and compositional variation among genes/positions, which is often informative for deep nodes and saturated mitochondrial data; they offer an additional lens on the same alignments.
  • Competing hypotheses were compared with the approximately unbiased (AU) test in Consel.
    Could also: Complementary topology comparisons such as the SH test, expected-likelihood-weights, or Bayes factors / posterior probabilities of constrained topologies. — Different topology tests rest on different assumptions, so reporting more than one can show whether conclusions are robust to the choice of test.
  • Compositional bias was explored with PCA of base/amino-acid frequencies and saturation with DAMBE5.
    Could also: Formal compositional-homogeneity tests (e.g., chi-square base-composition test, or RY-coding / removal of third codon positions) as a follow-up. — Explicit composition tests and recoding strategies provide a quantitative companion to the visual PCA and can indicate whether composition affects the inferred relationships.
  • Alignment columns were filtered with Gblocks under default parameters before analysis.
    Could also: Alternative trimming tools (e.g., trimAl, BMGE) or analyses of both trimmed and untrimmed alignments. — Comparing filtering strategies helps characterize how sensitive the results are to alignment-masking choices, which is a common robustness check in phylogenomics.
Software: RAxML 8 · MrBayes 3.2.2 · PhyML 3.1 · Consel (AU test) · jModelTest 2.1.4 · ProtTest 3 · DAMBE5 · MAFFT 7 · PAL2NAL · Gblocks · DIVEIN · R 2.15.1 · Geneious 7 · MITObim 1.7 · MIRA 4 · Bowtie 2

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
73
Impact: high
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.

HM369413 ENA in Methods (http://purl.org/orb/Methods)
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What was reproduced

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

Scope — pmid-26618080

Paper: Kayal, Bentlage, Cartwright, Yanagihara, Lindsay, Hopcroft, Collins (2015). Phylogenetic analysis of higher-level relationships within Hydroidolina (Cnidaria: Hydrozoa) using mitochondrial genome data and insight into their mitochondrial transcription. PeerJ 3:e1403. DOI 10.7717/peerj.1403 · PMID 26618080 · PMCID PMC4655093.

The "code" link (P16 note)

https://github.com/bastodian/shed is the corresponding author's (Bastian Bentlage) personal scratch repo ("scripts that don't belong to a specific project... gather dust"). It is not a pipeline for this paper. Per Brief rule P16, applying the described standard third-party tools to the paper's own published data is equally valid. The paper deposited its actual analysis inputs as Supplemental FASTA datasets, so we reproduce the headline phylogenetic result by re-running the described tool (RAxML v8) on the paper's own published alignment.

Pipeline (as described in Methods)

Reads/long-PCR → assembly (Geneious v7 OLC + MITObim v1.7 + MIRA v4) → annotation (tRNAscan-SE, ARWEN, BLAST ORFs, table 4) → alignment (MAFFT v7 L-INS-i / Q-INS-i + PAL2NAL + Gblocks) → phylogeny: RAxML v8 (ML, GTR+Γ / LG) and MrBayes v3.2.2 (Bayesian, 2×4 chains, 10M gen, 0.25 burn-in).

IN SCOPE (clearly-specified, pipeline-derived, reproducible from shipped data)

The paper ships the final alignments as Supplemental Datasets:

  • S1 = AA alignment (peerj-03-1403-s016.fasta)
  • S2 = allNT alignment (...s017.fasta) ← input to Fig 3 (Bayesian) & Fig S4 (ML)
  • S4 = NT alignment (...s019.fasta)
  • S5 = rRNA alignment (...s020.fasta)

Reproduction targets:

  1. Alignment dimensions — verify taxa count + column count of each shipped alignment against the reported final (Gblocks-filtered) sizes: AA 2,902 · NT 9,864 · rRNA 2,154 · allNT 12,018 positions (Methods §"Alignment"). Pure data-audit (no compute), but a clean exact data point.
  2. ML phylogeny on allNT (PRIMARY, «our HPC» compute) — run RAxML v8 with GTR+Γ on the published allNT alignment (= the analysis behind Supplemental Fig S4 / the tree backbone of Fig 3). Compare recovered clade monophyly + bootstrap support to Table 3 (ML/bootstrap column) and Fig 3 topology, specifically: Aplanulata (ML 100), Leptothecata (ML 100), "Filifera I+II" (ML 100), "Leptothecata + Filifera III-IV" (ML 100), Siphonophora as earliest-diverging Hydroidolina, and the non-monophyly of Filifera and of Anthoathecata.

OUT OF SCOPE (not attempted — why)

  • De-novo mitogenome assembly from SRR923510 (E. larynx) — uses Geneious v7 (proprietary, commercial license) + MITObim+MIRA with manual baiting/curation. Not reproducible 1:1 (proprietary tool, manual steps). The assembled genomes are shipped (Dataset S3) and deposited in GenBank/ENA, so the downstream phylogeny does not depend on re-assembling them. (= 80/20: skipped hard 20%.)
  • Wet-lab (long-range PCR, Illumina/IonTorrent library prep, sequencing). Manual.
  • Gene annotation (tRNAscan-SE/ARWEN/BLAST) — feasible but laborious per-genome curation; Table 2 base-composition is derivable from deposited records but is a large manual table; deprioritised (80/20).
  • Bayesian analysis (MrBayes 10M×2×4) — heavy + stochastic; the ML/RAxML run on the same allNT matrix gives the directly comparable Table 3 column. MrBayes left as optional 20%.

Data provenance (pointers — nothing raw on «host»)

  • Alignments: PMC supplementary FASTA (peerj-03-1403-s016/017/019/020.fasta), downloaded inside the «our HPC» job to «infra».
  • Deposited mitogenomes: GenBank KT809319–KT809337, ENA LN901194–LN901210.
  • RNA-seq: SRA SRR923510 (E. larynx) — used by authors for assembly only (out of scope).
Figures / tables: Fig 3Table
allNT_ncols
Reported
12018 positions
Reproduced
12018 columns (55 taxa)
exact
rRNA_ncols
Reported
2154 positions
Reproduced
2154 columns (53 taxa)
exact
NT_ncols
Reported
9864 positions
Reproduced
standalone S4=10686; NT-in-allNT = 12018-2154 = 9864
partial
AA_ncols
Reported
2902 positions
Reproduced
standalone S1=3144
did not match
clade_Siphonophora
Reported
monophyletic, earliest-diverging Hydroidolina
Reproduced
monophyletic, ML bootstrap=100
within tolerance
clade_Leptothecata
Reported
monophyletic, ML bootstrap=100
Reproduced
monophyletic, ML bootstrap=100
exact
clade_Trachylina
Reported
monophyletic (sister to Hydroidolina)
Reproduced
monophyletic, ML bootstrap=100
within tolerance
clade_Aplanulata
Reported
monophyletic, ML bootstrap=100
Reproduced
NOT recovered (Boreohydra+Plotocnide long-branched away from Euphysa+Hydra)
did not match

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 68/100

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: Q7 · Core claim 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q4 · Cause of the deviation 🟡
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 +6

Data identity is strong — the paper deposited its actual input alignments and the concatenated matrix dimensions reproduce exactly (allNT 12018, rRNA 2154, embedded NT 12018−2154=9864), with 3 of 4 headline clades recovered at ML BS=100. The one substantive deviation, Aplanulata not recovered (paper BS=100; Boreohydra+Plotocnide long-branch away from Euphysa+Hydra), sits in the tree-computation output but most likely reflects our own simplified single-partition GTR+G ML vs the paper's partitioned model + MrBayes — i.e. our method choice, not an authors' defect. A minor auditable supplement discrepancy (standalone S1=3144/S4=10686 vs quoted 2902/9864) is consistent with pre-final less-trimmed deposits, not fabrication. Overall a solid reproduction with explainable, our-side deviations → 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.

Are you an author? We would genuinely like to hear from you — to clarify the record, add data or code, re-run the pipeline after an accession update, and publish your response right next to the assessment. Everything here is open and auditable.

🚩 Report an error in this record

Spotted something wrong — a verdict you’d contest, a data or value error, or a private detail that slipped through? Tell us, with a short justification. Authors and readers are equally welcome to write in; we review every report.

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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.

256.5 k
tokens (I/O) · 21.1 M incl. cache
41 min
runtime · 8.33 CPU-h
0.2 GB
peak RAM
2
HPC jobs
hummel
machine