Evidence Receipt. Related Resources.
Compared to this week’s papers
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Page Freshness
Canonical route: /signal-canvas/development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods | Route /signal-canvas/development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methodsMCP example
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}Claims: 12
References: Pending verification
Proof: Verification pending
Freshness state: computing
PDF: https://arxiv.org/pdf/2603.26544v1
Source count: 3
Coverage: 33%
Last proof check: 2026-03-30T21:52:08.266Z
Signal Canvas receipt window
/buildability/development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods
Subject: Development of a European Union Time-Indexed Reference Dataset for Assessing the Performance of Signal Detection Methods in Pharmacovigilance using a Large Language Model
Preparing verified analysis
Dimensions overall score 7.0
No public code linked for this paper yet.
Development of a European Union Time-Indexed Reference Dataset for Assessing the Performance of Signal Detection Methods in Pharmacovigilance using a Large Language Model
This is the central theme and stated purpose of the study, clearly articulated in the title and abstract.
partial
This study addresses this gap by developing a time-indexed reference dataset for the European Union (EU), incorporating the timing of AE inclusion in product labels along with regulatory metadata.
The abstract explicitly states this as a key feature of the developed dataset.
partial
Section 4.8 was extracted and processed using DeepSeek V3 to identify AEs.
The abstract and methods section clearly state the LLM used and its function.
partial
The database includes 17,763 SmPC versions spanning 1995-2025, comprising 125,026 drug-AE associations.
Specific quantitative results are provided in the abstract.
partial
The time-indexed reference dataset, restricted to active products, included 1,479 medicinal products and 110,823 drug-AE associations.
Specific quantitative results are provided in the abstract.
partial
Most AEs were identified pre-marketing (74.5%) versus post-marketing (25.5%).
Specific quantitative results are provided in the abstract.
partial
Safety updates peaked around 2012.
A specific temporal result is stated in the abstract.
partial
The proposed dataset addresses a critical gap in pharmacovigilance by incorporating temporal information on AE recognition for the EU, supporting more accurate assessment of signal detection performance and facilitating methodological comparisons across analytical approaches.
This is a concluding statement in the abstract summarizing the significance of the work.
partial
Most AEs were identified pre-marketing (74.5%) versus post-marketing (25.5%).
The abstract presents a clear statistical finding regarding the timing of AE identification.
partial
Development of a European Union Time-Indexed Reference Dataset for Assessing the Performance of Signal Detection Methods in Pharmacovigilance using a Large Language Model
This is the central theme and stated purpose of the study, explicitly mentioned in the title and abstract.
partial
This study addresses this gap by developing a time-indexed reference dataset for the European Union (EU), incorporating the timing of AE inclusion in product labels along with regulatory metadata.
The abstract clearly states the dataset's composition, including the temporal aspect of AE inclusion and regulatory metadata.
partial
Section 4.8 was extracted and processed using DeepSeek V3 to identify AEs.
The abstract explicitly mentions the LLM used and its function in extracting AEs from SmPCs.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods
Paper ref
development-of-a-european-union-time-indexed-reference-dataset-for-assessing-the-performance-of-signal-detection-methods
arXiv id
2603.26544
Generated at
2026-03-30T21:52:08.266Z
Evidence freshness
stale
Last verification
2026-03-30T21:52:08.266Z
Sources
3
References
0
Coverage
33%
Lineage hash
4ec620711db2b99831ba5bbb62ece4b571128777e360c526efe3f68d1f15265c
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 3 sources / Verification pending
repo_url
references