Author: Admin

Machine Learning for Shadow Economy Detection — Classification of Suspicious Transaction Patterns

Posted on by Admin
Economic Research
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk  ·  DOI: 10.5281/zenodo.19513733  56stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI28%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,140✓Minimum 2,000 words for a full research article. Current: 2,140
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19513733
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]67%✓≥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 (41 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)

Detecting shadow economy activities through financial transaction monitoring is a critical challenge for regulators and financial institutions. This article investigates the application of machine l[REDACTED][REDACTED][REDACTED]g algorithms to classify suspicious transaction patterns, using synthetic transaction data that mimics real‑world features such as amount, frequency, and entropy. We pos...

Show moreHide
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk DOI: 10.5281/zenodo.19513733 56stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted67%○≥80% from verified, high-quality sources
[a]DOI28%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic56%○≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References18 refs✓Minimum 10 references required
[w]Words [REQ]2,140✓Minimum 2,000 words for a full research article. Current: 2,140
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19513733
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]67%✓≥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 (41 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)
Shadow Economy Dyn…Read More
Read more

The Fork Problem: When Community Splits Signal Innovation vs. Fragmentation

Posted on by Admin
Open Source Research
Open Source Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19489083  44stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access86%✓≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,062✓Minimum 2,000 words for a full research article. Current: 2,062
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19489083
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]77%✓≥60% of references from 2025–2026. Current: 77%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (21 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)

— title: “The Fork Problem: When Community Splits Signal Innovation vs. Fragmentation” author: “Oleh Ivchenko” series: “Trusted Open Source” — ## Abstract Open source software forks have long been viewed as existential threats to project stability, yet evidence increasingly suggests that forks serve dual roles: catalysts for innovation and sources...

Show moreHide
Open Source Research by Oleh Ivchenko DOI: 10.5281/zenodo.19489083 44stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted36%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic21%○≥80% from journals/conferences/preprints
[f]Free Access86%✓≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,062✓Minimum 2,000 words for a full research article. Current: 2,062
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19489083
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]77%✓≥60% of references from 2025–2026. Current: 77%
[c]Data Charts4✓Original data charts from reproducible analysis (min 2). Current: 4
[g]Code✓✓Source code available on GitHub
[m]Diagrams2✓Mermaid architecture/flow diagrams. Current: 2
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (21 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)
Trusted Open SourceRead More
Read more

Closing the Gap: Evidence-Based Strategies That Actually Work

Posted on by Admin
Gap Research
Gap Research by Oleh Ivchenko  67stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted100%✓≥80% from verified, high-quality sources
[a]DOI67%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed67%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]2,587✓Minimum 2,000 words for a full research article. Current: 2,587
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts2✓Original data charts from reproducible analysis (min 2). Current: 2
[g]Code✓✓Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (74 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)

Evidence-based strategies transform AI adoption from aspiration into measurable outcomes Stabilarity Research Hub April 2026 DOI: 10.5281/zenodo.19117123 Abstract The capability-adoption gap in artificial intelligence is well-documented but poorly addressed. While organizations invest heavily in AI development and deployment, measurable adoption rates consistently lag behind projected capabilit...

Show moreHide
Gap Research by Oleh Ivchenko 67stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted100%✓≥80% from verified, high-quality sources
[a]DOI67%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed67%○≥80% have metadata indexed
[l]Academic67%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]2,587✓Minimum 2,000 words for a full research article. Current: 2,587
[d]DOI [REQ]✗✗Zenodo DOI registered for persistent citation
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]100%✓≥60% of references from 2025–2026. Current: 100%
[c]Data Charts2✓Original data charts from reproducible analysis (min 2). Current: 2
[g]Code✓✓Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (74 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)
Capability-Adoptio…Read More
Read more

Production Cache Monitoring — Metrics and Capacity Planning

Posted on by Admin
Technical Research
Technical Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19340506  71stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources44%○≥80% from editorially reviewed sources
[t]Trusted68%○≥80% from verified, high-quality sources
[a]DOI52%○≥80% have a Digital Object Identifier
[b]CrossRef48%○≥80% indexed in CrossRef
[i]Indexed68%○≥80% have metadata indexed
[l]Academic64%○≥80% from journals/conferences/preprints
[f]Free Access60%○≥80% are freely accessible
[r]References25 refs✓Minimum 10 references required
[w]Words [REQ]2,611✓Minimum 2,000 words for a full research article. Current: 2,611
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19340506
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]74%✓≥60% of references from 2025–2026. Current: 74%
[c]Data Charts5✓Original data charts from reproducible analysis (min 2). Current: 5
[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 (66 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)

As key-value (KV) cache systems become the dominant memory consumer in production large language model (LLM) inference, the ability to monitor cache behavior and plan capacity proactively determines whether deployments meet service-level objectives (SLOs) or suffer unpredictable degradation. This article investigates three research questions addressing (1) which monitoring metrics most reliably...

Show moreHide
Technical Research by Oleh Ivchenko DOI: 10.5281/zenodo.19340506 71stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources44%○≥80% from editorially reviewed sources
[t]Trusted68%○≥80% from verified, high-quality sources
[a]DOI52%○≥80% have a Digital Object Identifier
[b]CrossRef48%○≥80% indexed in CrossRef
[i]Indexed68%○≥80% have metadata indexed
[l]Academic64%○≥80% from journals/conferences/preprints
[f]Free Access60%○≥80% are freely accessible
[r]References25 refs✓Minimum 10 references required
[w]Words [REQ]2,611✓Minimum 2,000 words for a full research article. Current: 2,611
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19340506
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]74%✓≥60% of references from 2025–2026. Current: 74%
[c]Data Charts5✓Original data charts from reproducible analysis (min 2). Current: 5
[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 (66 × 60%) + Required (4/5 × 30%) + Optional (3/4 × 10%)
AI MemoryRead More
Read more

Tax Evasion Mechanisms in Ukraine: A Typology of Shadow Economy Channels

Posted on by Admin
Economic Research
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk  ·  DOI: 10.5281/zenodo.19229248  55stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources35%○≥80% from editorially reviewed sources
[t]Trusted48%○≥80% from verified, high-quality sources
[a]DOI52%○≥80% have a Digital Object Identifier
[b]CrossRef35%○≥80% indexed in CrossRef
[i]Indexed48%○≥80% have metadata indexed
[l]Academic52%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]2,522✓Minimum 2,000 words for a full research article. Current: 2,522
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19229248
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]50%✗≥60% of references from 2025–2026. Current: 50%
[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 (53 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)

Ukraine's shadow economy remains one of the largest in Europe, with wartime conditions creating both new evasion channels and shifting the composition of existing ones. This article develops a comprehensive typology of tax evasion mechanisms operating in Ukraine, classifying shadow economy channels along three dimensions: mechanism type, sectoral concentration, and detection difficulty. Drawing...

Show moreHide
Economic Research by Oleh Ivchenko, Iryna Ivchenko & Dmytro Grybeniuk DOI: 10.5281/zenodo.19229248 55stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources35%○≥80% from editorially reviewed sources
[t]Trusted48%○≥80% from verified, high-quality sources
[a]DOI52%○≥80% have a Digital Object Identifier
[b]CrossRef35%○≥80% indexed in CrossRef
[i]Indexed48%○≥80% have metadata indexed
[l]Academic52%○≥80% from journals/conferences/preprints
[f]Free Access91%✓≥80% are freely accessible
[r]References23 refs✓Minimum 10 references required
[w]Words [REQ]2,522✓Minimum 2,000 words for a full research article. Current: 2,522
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19229248
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]50%✗≥60% of references from 2025–2026. Current: 50%
[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 (53 × 60%) + Required (3/5 × 30%) + Optional (2/4 × 10%)
Shadow Economy Dyn…Read More
Read more

The Open Humanoid Manifesto: An Open-Source Blueprint for Accessible Humanoid Robotics

Posted on by Admin
Engineering Research
Engineering Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.19157578  54stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted58%○≥80% from verified, high-quality sources
[a]DOI32%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed89%✓≥80% have metadata indexed
[l]Academic53%○≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References19 refs✓Minimum 10 references required
[w]Words [REQ]2,958✓Minimum 2,000 words for a full research article. Current: 2,958
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19157578
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]28%✗≥60% of references from 2025–2026. Current: 28%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (56 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The humanoid robotics field stands at an inflection point: global market projections exceed two billion dollars in 2026, yet the engineering knowledge required to build a functional bipedal robot remains concentrated within a small number of well-funded corporations and elite research laboratories. This article presents the Open Humanoid Manifesto — a comprehensive open-source blueprint that sy...

Show moreHide
Engineering Research by Oleh Ivchenko DOI: 10.5281/zenodo.19157578 54stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted58%○≥80% from verified, high-quality sources
[a]DOI32%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed89%✓≥80% have metadata indexed
[l]Academic53%○≥80% from journals/conferences/preprints
[f]Free Access89%✓≥80% are freely accessible
[r]References19 refs✓Minimum 10 references required
[w]Words [REQ]2,958✓Minimum 2,000 words for a full research article. Current: 2,958
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.19157578
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]28%✗≥60% of references from 2025–2026. Current: 28%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (56 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Open HumanoidRead More
Read more

Sensing and Perception: IMU, Depth Cameras, Force-Torque Sensors, and Sensor Fusion for Humanoid Robots

Posted on by Admin
Engineering Research
Engineering Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18978273  52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted70%○≥80% from verified, high-quality sources
[a]DOI10%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed70%○≥80% have metadata indexed
[l]Academic70%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References10 refs✓Minimum 10 references required
[w]Words [REQ]2,185✓Minimum 2,000 words for a full research article. Current: 2,185
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18978273
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]9%✗≥60% of references from 2025–2026. Current: 9%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (3/5 × 30%) + Optional (1/4 × 10%)

Reliable locomotion and manipulation in a bipedal humanoid robot depend fundamentally on the quality, latency, and fusion of sensory data. This article presents the sensing and perception subsystem specification for the Open Humanoid platform, covering inertial measurement units (IMUs), stereo depth cameras, six-axis force-torque sensors, tactile arrays, and joint encoders. We analyse sensor pl...

Show moreHide
Engineering Research by Oleh Ivchenko DOI: 10.5281/zenodo.18978273 52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted70%○≥80% from verified, high-quality sources
[a]DOI10%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed70%○≥80% have metadata indexed
[l]Academic70%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References10 refs✓Minimum 10 references required
[w]Words [REQ]2,185✓Minimum 2,000 words for a full research article. Current: 2,185
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18978273
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]9%✗≥60% of references from 2025–2026. Current: 9%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (3/5 × 30%) + Optional (1/4 × 10%)
Open HumanoidRead More
Read more

Review: Beyond the Illusion of Consensus — What the LLM-as-a-Judge Paradigm Gets Dangerously Wrong

Posted on by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18973500  52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI22%○≥80% have a Digital Object Identifier
[b]CrossRef11%○≥80% indexed in CrossRef
[i]Indexed78%○≥80% have metadata indexed
[l]Academic78%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References9 refs○Minimum 10 references required
[w]Words [REQ]1,717✗Minimum 2,000 words for a full research article. Current: 1,717
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18973500
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]10%✗≥60% of references from 2025–2026. Current: 10%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (62 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

Song, Zheng, and Xu (2026) argue that the LLM-as-a-judge paradigm rests on a fundamentally flawed assumption: that high inter-evaluator agreement signals reliable, objective evaluation. Through a large-scale empirical study involving 105,600 evaluation instances (32 LLMs evaluated across 3 frontier judges, 100 tasks, and 11 temperature settings), they introduce "Evaluation Illusion," wherein ju...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18973500 52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted78%○≥80% from verified, high-quality sources
[a]DOI22%○≥80% have a Digital Object Identifier
[b]CrossRef11%○≥80% indexed in CrossRef
[i]Indexed78%○≥80% have metadata indexed
[l]Academic78%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References9 refs○Minimum 10 references required
[w]Words [REQ]1,717✗Minimum 2,000 words for a full research article. Current: 1,717
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18973500
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]10%✗≥60% of references from 2025–2026. Current: 10%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (62 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Measuring State Fragility: An Empirical RSI Framework Applied to Ukraine

Posted on by Admin
Geopolitical Research
Geopolitical Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18998198  34stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI33%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]1,262✗Minimum 2,000 words for a full research article. Current: 1,262
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18998198
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]25%✗≥60% of references from 2025–2026. Current: 25%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (32 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

We built something. Not a dashboard, not a report, not another data visualization that looks impressive but tells you nothing actionable. We built a ruler. A ruler that measures the same thing — instability — whether you point it at a country, a city, or a neighbourhood. The same 0-to-1 scale. The same formula. The same question: how close is this place to falling apart?

Show moreHide
Geopolitical Research by Oleh Ivchenko DOI: 10.5281/zenodo.18998198 34stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI33%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References3 refs○Minimum 10 references required
[w]Words [REQ]1,262✗Minimum 2,000 words for a full research article. Current: 1,262
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18998198
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]25%✗≥60% of references from 2025–2026. Current: 25%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (32 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Geopolitical RiskRead More
Read more