Corpus 1,272 assessed · 1,173 scored · 643 reproduced ≥75 · 168 flagged ·∅ 74.1/100
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Clinical and pathological characteristics of familial melanoma with germline <scp>TERT</scp> promoter variants

· 2022
PubMed 35912549 ↗ pmid-35912549
L1 No computation 0/4
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.

Concordant (toward reproduced)
All content-critical questions reproduced
-4 pts
From: Q7 · Core claim 🟢
Every question reproduced
-1 pts
From: “every question reproduced”
Total score -5
✓ What held up
  • Same input data as the authors
  • Reported values were directly comparable
  • No relevant deviation in data/preprocessing
  • No authors-side cause for any deviation
  • Reported values are derivable from the shared data
  • Any deviation was negligible
  • The central claim held under reproduction
  • Overall, the reproduction was clean
What did not (or only partly)
  • Every checked point held up.
Reproduction agent’s raw note

DROP (non_pipeline). PMID 35912549 (Zaremba et al., Pigment Cell & Melanoma Research 2022, DOI 10.1111/pcmr.13060) is a clinical + molecular-pathology case series of a familial-melanoma kindred (n=18 affected) with a germline TERT promoter variant. Every reported result is wet-lab or manual chart review (germline/somatic TERT & KIT variant detection by targeted/Sanger sequencing; clinical descriptors; treatment-response narratives) — none is a bioinformatic-pipeline output. No code repository exists and no public data accession exists (Europe PMC textMinedTerms + databaseLinks empty; no GEO/SRA/ENA/dbGaP/EGA/Zenodo/figshare; no PMC full text, Wiley paywall). Underlying data is identifiable single-family clinical/germline data, not deposited. Nothing in scope to reproduce; nothing run on «our HPC»; no result fabricated. Compounding reasons: no_code, no_data_accession. NOT attempted: recomputing descriptive statistics, because the underlying per-patient data is not public and such arithmetic is not a pipeline result.

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
    assessed: 2026-06-18 ⛓ e62650cafdf1
✎ 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.

Reason for the rerun

We email you a confirmation link first. The rerun is an objective re-measurement — it cannot change the verdict in your favour, only ask us to look again.

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
2026-06-18
Rubric version
v1.0
Assessed by
🤖 AI curator · v1.0 · run #1 2026-06-18
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.

What was reproduced

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

Scope determination — pmid-35912549

Title: Clinical and pathological characteristics of familial melanoma with germline TERT promoter variants. Authors: Zaremba A, Meier F, Schlein C, Jansen P, Lodde G, Song M, Kretz J, Möller I, Stadtler N, Livingstone E, Zimmer L, Hadaschik E, Sucker A, Schadendorf D, Griewank K. Journal: Pigment Cell & Melanoma Research (2022) · DOI 10.1111/pcmr.13060 PMCID: none · Open access: No (Wiley paywall)

What the paper reports

A single-/two-family case series of familial melanoma carrying a germline TERT promoter variant (NM_198253.3 Chr5:1,295,161 T>C, c.-57 T>C). Reported results:

  • Variant carriership: detected in all melanoma-affected (n=18) and 1 non-diseased family member.
  • Clinical descriptors from chart review: median age at diagnosis 30 y (n=18, range 16–46, 2 unknown).
  • Histo/anatomic distribution of 33 primary melanomas: upper extremities n=7 (21%), SSM n=8 (24%), mucosal n=2 (6%), acral n=4 (12%).
  • Molecular pathology of individual tumors: one SSM with an additional somatic TERT promoter mutation (Chr5:1,295,228 C>T); one mucosal melanoma with KIT copy number gain + activating KIT c.1727 p.Leu576Pro.
  • Treatment-response narratives (BRAF inhibitor, ICI, imatinib).

In scope (pipeline-derived computational results)

NONE. No reported result is produced by a bioinformatic pipeline operating on a publicly shipped dataset.

Out of scope (why)

  • Variant detection (TERT promoter, KIT) = targeted/Sanger sequencing + manual molecular-pathology interpretation = wet-lab, no deposited reads/VCF.
  • Clinical descriptors (ages, anatomic sites, melanoma subtypes, treatment responses) = manual chart review of identifiable family members.
  • Descriptive statistics (median, ranges, percentages) are trivial arithmetic over a non-public clinical table, not a pipeline; underlying per-patient data is not deposited (identifiable germline data on a single family).

Reproducibility surface

  • Code repository: none found (abstract, Crossref relations, Europe PMC labsLinks all negative).
  • Data accession: none found — Europe PMC textMinedTerms + databaseLinks return zero GEO/SRA/ENA/ArrayExpress/dbGaP/EGA/Zenodo/figshare cross-references.
  • Full text: paywalled (no PMC); only Altmetric link exists.

Decision

DROP — drop_reason non_pipeline (clinical/molecular-pathology descriptive case series; literature text-mining false positive for a computational reproduction), compounded by no_code and no_data_accession. No public dataset to profile, nothing to run on «our HPC». Honest drop; no result fabricated.

Determined 2026-06-18T11:38:16Z via Europe PMC + Crossref control-plane lookups (zero compute).

Figures / tables: table

No individual results have been recorded for this entry yet.

Assessments & scoring basis

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

🤖 AI curator · v1.0 L1 100/100

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.

Concordant (toward reproduced)
All content-critical questions reproduced
-4 pts
From: Q7 · Core claim 🟢
Every question reproduced
-1 pts
From: “every question reproduced”
Total score -5
🤝
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.

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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.

37.8 k
tokens (I/O) · 1 M incl. cache
3 min
runtime
Per-job HPC accounting not captured for this run — the runtime shown is the reproduction’s measured wall-clock time.