Fresh Repositories Watch: Legal Technology — Contract Analysis and Compliance

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19445010  80stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources14%○≥80% from editorially reviewed sources
[t]Trusted82%✓≥80% from verified, high-quality sources
[a]DOI64%○≥80% have a Digital Object Identifier
[b]CrossRef14%○≥80% indexed in CrossRef
[i]Indexed73%○≥80% have metadata indexed
[l]Academic68%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References22 refs✓Minimum 10 references required
[w]Words [REQ]1,939✓Minimum 1,000 words of article body. Current: 1,939
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]12✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 12
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19445010
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness81%✓≥60% of references from 2025–2026. Current: 81%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (72 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

Legal technology is undergoing a fundamental transformation: open-source repositories for contract analysis, clause classification, and regulatory compliance (related: Peer Review Automation) have grown from a niche academic concern to a production-critical infrastructure layer. This article surveys open-source legal technology repositories created or significantly updated in 2025-2026, evaluat...

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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.19445010 80stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources14%○≥80% from editorially reviewed sources
[t]Trusted82%✓≥80% from verified, high-quality sources
[a]DOI64%○≥80% have a Digital Object Identifier
[b]CrossRef14%○≥80% indexed in CrossRef
[i]Indexed73%○≥80% have metadata indexed
[l]Academic68%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References22 refs✓Minimum 10 references required
[w]Words [REQ]1,939✓Minimum 1,000 words of article body. Current: 1,939
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]12✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 12
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19445010
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness81%✓≥60% of references from 2025–2026. Current: 81%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (72 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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Public Trust Metrics for Research Platforms: From Badge Scores to Community Credibility

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Quality Research
Quality Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19434311  86stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources64%○≥80% from editorially reviewed sources
[t]Trusted84%✓≥80% from verified, high-quality sources
[a]DOI72%○≥80% have a Digital Object Identifier
[b]CrossRef68%○≥80% indexed in CrossRef
[i]Indexed76%○≥80% have metadata indexed
[l]Academic72%○≥80% from journals/conferences/preprints
[f]Free Access96%✓≥80% are freely accessible
[r]References25 refs✓Minimum 10 references required
[w]Words [REQ]2,600✓Minimum 1,000 words of article body. Current: 2,600
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]17✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 17
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19434311
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness65%✓≥60% of references from 2025–2026. Current: 65%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (81 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The credibility of research platforms depends not only on the quality of individual publications but on systematic, measurable signals that allow readers, institutions, and policymakers to calibrate trust. This article examines how multi-dimensional badge scoring systems — exemplified by the STABIL framework — translate article-level quality evidence into platform-level credibility, and how com...

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Quality Research by Oleh Ivchenko DOI: 10.5281/zenodo.19434311 86stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources64%○≥80% from editorially reviewed sources
[t]Trusted84%✓≥80% from verified, high-quality sources
[a]DOI72%○≥80% have a Digital Object Identifier
[b]CrossRef68%○≥80% indexed in CrossRef
[i]Indexed76%○≥80% have metadata indexed
[l]Academic72%○≥80% from journals/conferences/preprints
[f]Free Access96%✓≥80% are freely accessible
[r]References25 refs✓Minimum 10 references required
[w]Words [REQ]2,600✓Minimum 1,000 words of article body. Current: 2,600
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]17✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 17
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19434311
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness65%✓≥60% of references from 2025–2026. Current: 65%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (81 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
Article Quality Sc…Read More
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Peer Review Automation: Combining Rule-Based Validation with LLM-Assisted Quality Assessment

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Quality Research
Quality Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19433308  65stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources6%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed28%○≥80% have metadata indexed
[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]3,720✓Minimum 1,000 words of article body. Current: 3,720
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]9✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 9
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19433308
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (47 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The scalability crisis in academic peer review — where submission volumes grow 8–12% annually while reviewer pools stagnate — demands systematic automation without sacrificing the scientific rigor that peer review is designed to enforce. This article examines how hybrid systems combining deterministic rule-based validators with large language model (LLM)-assisted semantic evaluation can address...

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Quality Research by Oleh Ivchenko DOI: 10.5281/zenodo.19433308 65stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources6%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed28%○≥80% have metadata indexed
[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]3,720✓Minimum 1,000 words of article body. Current: 3,720
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]9✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 9
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19433308
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (47 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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Fresh Repositories Watch: Climate and Energy — Sustainability Optimization Models

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19432328  88stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources65%○≥80% from editorially reviewed sources
[t]Trusted87%✓≥80% from verified, high-quality sources
[a]DOI78%○≥80% have a Digital Object Identifier
[b]CrossRef52%○≥80% indexed in CrossRef
[i]Indexed83%✓≥80% have metadata indexed
[l]Academic74%○≥80% from journals/conferences/preprints
[f]Free Access83%✓≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]1,867✓Minimum 1,000 words of article body. Current: 1,867
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]15✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 15
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19432328
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness83%✓≥60% of references from 2025–2026. Current: 83%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (84 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The intersection of open-source software development and climate science has produced a growing ecosystem of tools for energy system optimization, carbon emissions tracking, and renewable energy forecasting. This article surveys the state of open-source repositories in the climate and energy domain as of April 2026, examining eleven repositories across five functional categories: energy grid op...

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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.19432328 88stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources65%○≥80% from editorially reviewed sources
[t]Trusted87%✓≥80% from verified, high-quality sources
[a]DOI78%○≥80% have a Digital Object Identifier
[b]CrossRef52%○≥80% indexed in CrossRef
[i]Indexed83%✓≥80% have metadata indexed
[l]Academic74%○≥80% from journals/conferences/preprints
[f]Free Access83%✓≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]1,867✓Minimum 1,000 words of article body. Current: 1,867
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]15✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 15
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19432328
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness83%✓≥60% of references from 2025–2026. Current: 83%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (84 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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Fresh Repositories Watch: Healthcare AI — Emerging Tools Under 60 Days Old

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Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19430103  87stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources61%○≥80% from editorially reviewed sources
[t]Trusted87%✓≥80% from verified, high-quality sources
[a]DOI81%✓≥80% have a Digital Object Identifier
[b]CrossRef61%○≥80% indexed in CrossRef
[i]Indexed77%○≥80% have metadata indexed
[l]Academic81%✓≥80% from journals/conferences/preprints
[f]Free Access58%○≥80% are freely accessible
[r]References31 refs✓Minimum 10 references required
[w]Words [REQ]3,497✓Minimum 1,000 words of article body. Current: 3,497
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]21✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 21
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19430103
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness31%○≥60% of references from 2025–2026. Current: 31%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (85 × 60%) + Required (4/4 × 30%) + Optional (4/7 × 10%)

This article continues the Trusted Open Source series by applying the STABIL scoring methodology — introduced in our foundational index — to a dynamic subset of the open-source ecosystem: repositories less than 60 days old. We focus specifically on Healthcare AI, a domain where open-source tooling has seen a measurable acceleration in the first quarter of 2026. Three research questions guide th...

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Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.19430103 87stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources61%○≥80% from editorially reviewed sources
[t]Trusted87%✓≥80% from verified, high-quality sources
[a]DOI81%✓≥80% have a Digital Object Identifier
[b]CrossRef61%○≥80% indexed in CrossRef
[i]Indexed77%○≥80% have metadata indexed
[l]Academic81%✓≥80% from journals/conferences/preprints
[f]Free Access58%○≥80% are freely accessible
[r]References31 refs✓Minimum 10 references required
[w]Words [REQ]3,497✓Minimum 1,000 words of article body. Current: 3,497
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]21✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 21
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19430103
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness31%○≥60% of references from 2025–2026. Current: 31%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (85 × 60%) + Required (4/4 × 30%) + Optional (4/7 × 10%)
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Freshness Decay in Academic References: Measuring Citation Shelf Life Across AI Research Domains

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Quality Research
Quality Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19428758  66stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted47%○≥80% from verified, high-quality sources
[a]DOI24%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed71%○≥80% have metadata indexed
[l]Academic53%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References17 refs✓Minimum 10 references required
[w]Words [REQ]2,400✓Minimum 1,000 words of article body. Current: 2,400
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]8✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 8
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19428758
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness73%✓≥60% of references from 2025–2026. Current: 73%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The lifespan of a scientific reference is finite. In fast-moving fields like artificial intelligence, a citation that was cutting-edge eighteen months ago may today represent outdated or superseded knowledge. This article introduces the concept of freshness decay — the progressive reduction in the epistemic relevance of a reference as its publication age increases — and develops a quantitative ...

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Quality Research by Oleh Ivchenko DOI: 10.5281/zenodo.19428758 66stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted47%○≥80% from verified, high-quality sources
[a]DOI24%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed71%○≥80% have metadata indexed
[l]Academic53%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References17 refs✓Minimum 10 references required
[w]Words [REQ]2,400✓Minimum 1,000 words of article body. Current: 2,400
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]8✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 8
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19428758
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness73%✓≥60% of references from 2025–2026. Current: 73%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (48 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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The STABIL Badge System: A Multi-Dimensional Framework for Quantifying Research Article Trust

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Quality Research
Quality Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19427380  69stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources6%○≥80% from editorially reviewed sources
[t]Trusted81%✓≥80% from verified, high-quality sources
[a]DOI38%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed31%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access88%✓≥80% are freely accessible
[r]References16 refs✓Minimum 10 references required
[w]Words [REQ]2,204✓Minimum 1,000 words of article body. Current: 2,204
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]9✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 9
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19427380
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness69%✓≥60% of references from 2025–2026. Current: 69%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (53 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

In the previous article, we established that automated citation validation using CrossRef, DOI resolution, and source classification provides a quantitative foundation for reference quality assessment. Building on that foundation, this article introduces the STABIL badge system — a multi-dimensional scoring framework designed to quantify the overall trustworthiness of scientific research articl...

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Quality Research by Oleh Ivchenko DOI: 10.5281/zenodo.19427380 69stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources6%○≥80% from editorially reviewed sources
[t]Trusted81%✓≥80% from verified, high-quality sources
[a]DOI38%○≥80% have a Digital Object Identifier
[b]CrossRef6%○≥80% indexed in CrossRef
[i]Indexed31%○≥80% have metadata indexed
[l]Academic50%○≥80% from journals/conferences/preprints
[f]Free Access88%✓≥80% are freely accessible
[r]References16 refs✓Minimum 10 references required
[w]Words [REQ]2,204✓Minimum 1,000 words of article body. Current: 2,204
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]9✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 9
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19427380
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness69%✓≥60% of references from 2025–2026. Current: 69%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (53 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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UIB Open-Source Benchmark Suite: Evaluation Protocol, Reproducibility Guarantees, and Community Validation

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Benchmark Research
Benchmark Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19425176  70stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI56%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed17%○≥80% have metadata indexed
[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,202✓Minimum 1,000 words of article body. Current: 2,202
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]11✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 11
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19425176
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness73%✓≥60% of references from 2025–2026. Current: 73%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (54 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The Universal Intelligence Benchmark (UIB) theoretical framework, dimensional taxonomy, and composite scoring formula have been developed across nine preceding articles in this series. This article completes the framework by presenting the UIB Open-Source Benchmark Suite — the concrete evaluation infrastructure that operationalizes those concepts for independent replication. We address three re...

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Benchmark Research by Oleh Ivchenko DOI: 10.5281/zenodo.19425176 70stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI56%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
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[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,202✓Minimum 1,000 words of article body. Current: 2,202
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]11✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 11
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19425176
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness73%✓≥60% of references from 2025–2026. Current: 73%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (54 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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The UIB Composite Score: Integration Across All Dimensions

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Benchmark Research
Benchmark Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19423466  70stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI44%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed28%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,370✓Minimum 1,000 words of article body. Current: 2,370
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]12✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 12
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19423466
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness69%✓≥60% of references from 2025–2026. Current: 69%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (55 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

The Universal Intelligence Benchmark (UIB) has systematically developed eight intelligence dimensions over the course of this series: causal reasoning, embodied grounding, temporal planning, social cognition, resource efficiency, linguistic reasoning, multimodal perception, and meta-learning. This article presents the mathematical framework for integrating these dimensions into a single UIB Com...

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Benchmark Research by Oleh Ivchenko DOI: 10.5281/zenodo.19423466 70stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI44%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed28%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,370✓Minimum 1,000 words of article body. Current: 2,370
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]12✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 12
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19423466
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness69%✓≥60% of references from 2025–2026. Current: 69%
[c]Data Charts3✓Original data charts from reproducible analysis (min 2). Current: 3
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (55 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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Measuring Adoption Velocity: Metrics and Benchmarks Across Industries

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Gap Research
Gap Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19423051  61stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted53%○≥80% from verified, high-quality sources
[a]DOI29%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic35%○≥80% from journals/conferences/preprints
[f]Free Access71%○≥80% are freely accessible
[r]References17 refs✓Minimum 10 references required
[w]Words [REQ]2,548✓Minimum 1,000 words of article body. Current: 2,548
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]11✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 11
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19423051
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (39 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)

Adoption velocity — the rate at which organisations move from AI awareness to scaled deployment — has emerged as a critical differentiator between enterprises that extract compounding value from artificial intelligence and those perpetually stuck in pilot limbo. In the previous article, we established that the training gap is the primary human-side barrier to AI deployment; here we turn to meas...

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Gap Research by Oleh Ivchenko DOI: 10.5281/zenodo.19423051 61stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted53%○≥80% from verified, high-quality sources
[a]DOI29%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic35%○≥80% from journals/conferences/preprints
[f]Free Access71%○≥80% are freely accessible
[r]References17 refs✓Minimum 10 references required
[w]Words [REQ]2,548✓Minimum 1,000 words of article body. Current: 2,548
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]11✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 11
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19423051
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness67%✓≥60% of references from 2025–2026. Current: 67%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (39 × 60%) + Required (4/4 × 30%) + Optional (5/7 × 10%)
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