Diagram showing how ML integrates into medical image analysis workflow from acquisition to diagnosis

Image Classification and ML in Disease Recognition: A Research Review

Posted on by Admin
Medical Research
Medical Research by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18752910  52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources43%○≥80% from editorially reviewed sources
[t]Trusted71%○≥80% from verified, high-quality sources
[a]DOI57%○≥80% have a Digital Object Identifier
[b]CrossRef29%○≥80% indexed in CrossRef
[i]Indexed57%○≥80% have metadata indexed
[l]Academic57%○≥80% from journals/conferences/preprints
[f]Free Access57%○≥80% are freely accessible
[r]References7 refs○Minimum 10 references required
[w]Words [REQ]1,994✗Minimum 2,000 words for a full research article. Current: 1,994
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752910
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (63 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

A comprehensive review of machine learning in medical image analysis, examining which ML techniques apply at each diagnostic stage, evidence-based best practices for doctor-AI collaboration, and unique conclusions on reducing diagnostic errors.

Show moreHide
Medical Research by Oleh Ivchenko DOI: 10.5281/zenodo.18752910 52stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources43%○≥80% from editorially reviewed sources
[t]Trusted71%○≥80% from verified, high-quality sources
[a]DOI57%○≥80% have a Digital Object Identifier
[b]CrossRef29%○≥80% indexed in CrossRef
[i]Indexed57%○≥80% have metadata indexed
[l]Academic57%○≥80% from journals/conferences/preprints
[f]Free Access57%○≥80% are freely accessible
[r]References7 refs○Minimum 10 references required
[w]Words [REQ]1,994✗Minimum 2,000 words for a full research article. Current: 1,994
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752910
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (63 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Medical ML DiagnosisRead More
Read more
Chart comparing AI model training costs from GPT-4 at 00M+ to DeepSeek-R1 at /usr/bin/bash.25M

Cost-Effective AI Development: A Research Review

Posted on by Admin
DOI: 10.5281/zenodo.18752912  15stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]640✗Minimum 2,000 words for a full research article. Current: 640
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752912
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

A comprehensive review of research on cost-effective AI development, examining how organizations achieve state-of-the-art capabilities at 400x lower costs through techniques like RLVR, MoE architectures, and open-weight models.

Show moreHide
DOI: 10.5281/zenodo.18752912 15stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]640✗Minimum 2,000 words for a full research article. Current: 640
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752912
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Read More
Read more

🚀 StabilarityHub Leads International MedAI Hackathon 2025: Transforming Healthcare with AI

Posted on by Admin
DOI: 10.5281/zenodo.18752914  22stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted13%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access38%○≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]893✗Minimum 2,000 words for a full research article. Current: 893
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752914
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]17%✗≥60% of references from 2025–2026. Current: 17%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (16 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Celebrating the International MedAI Hackathon 2025 — where 50+ innovators from Ukraine, Germany and beyond collaborated to build transformative AI solutions in radiology, mental health, and healthcare operations. Led by StabilarityHub with ONPU, GROMUS, Innova Clinics, and ScanLab. Discover the winning projects and the future of healthcare technology.

Show moreHide
DOI: 10.5281/zenodo.18752914 22stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted13%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed13%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access38%○≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]893✗Minimum 2,000 words for a full research article. Current: 893
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752914
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]17%✗≥60% of references from 2025–2026. Current: 17%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (16 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more

2025 AI Research Impact: A Year of Transformation

Posted on by Admin
DOI: 10.5281/zenodo.18752916  32stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI17%○≥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 Access83%✓≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]1,630✗Minimum 2,000 words for a full research article. Current: 1,630
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752916
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[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 (29 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

2025 marked a fundamental shift in artificial intelligence research—transitioning from "powerful tool" to "fundamental infrastructure." This comprehensive review examines the year's transformative achievements across model efficiency, reasoning capabilities, multimodal intelligence, and real-world deployment. We analyze key breakthroughs including the evolution of the Gemini model series, the e...

Show moreHide
DOI: 10.5281/zenodo.18752916 32stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI17%○≥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 Access83%✓≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]1,630✗Minimum 2,000 words for a full research article. Current: 1,630
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752916
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[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 (29 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
Read More
Read more

Google Antigravity: Redefining AI-Assisted Software Development

Posted on by Admin
DOI: 10.5281/zenodo.18752918  13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]250✗Minimum 2,000 words for a full research article. Current: 250
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752918
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Google Antigravity, launched November 2025, represents the next generation of AI-assisted coding. It's not a tool that suggests code—it's a developer that works alongside you.

Show moreHide
DOI: 10.5281/zenodo.18752918 13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]250✗Minimum 2,000 words for a full research article. Current: 250
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752918
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more

Pixel 10 & AI Integration: The Agentic Phone Era Begins

Posted on by Admin
DOI: 10.5281/zenodo.18752920  31stabilfr·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]218✗Minimum 2,000 words for a full research article. Current: 218
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752920
[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]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (32 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Pixel 10 represents a watershed moment: the first phone designed from the ground up to be an agentic device. It's not just running AI—it's an AI that runs a phone.

Show moreHide
DOI: 10.5281/zenodo.18752920 31stabilfr·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]218✗Minimum 2,000 words for a full research article. Current: 218
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752920
[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]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (32 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more

AI Transforming Science: Math, Biology, and Discovery 2025

Posted on by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18748877  35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources13%○≥80% from editorially reviewed sources
[t]Trusted25%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed25%○≥80% have metadata indexed
[l]Academic25%○≥80% from journals/conferences/preprints
[f]Free Access38%○≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]2,997✓Minimum 2,000 words for a full research article. Current: 2,997
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18748877
[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 (24 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

2025 marked a watershed year for AI-driven scientific discovery, with systems transitioning from computational tools to active research partners. Google DeepMind's AlphaEvolve discovered novel algorithms for fundamental mathematical and computational problems, improving efficiency across Google's infrastructure by 0.7% globally and finding new solutions to open problems that have challenged mat...

Show moreHide
Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18748877 35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources13%○≥80% from editorially reviewed sources
[t]Trusted25%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed25%○≥80% have metadata indexed
[l]Academic25%○≥80% from journals/conferences/preprints
[f]Free Access38%○≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]2,997✓Minimum 2,000 words for a full research article. Current: 2,997
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18748877
[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 (24 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
Future of AIRead More
Read more

Gemini 3: Google’s Leap in Reasoning and Multimodal AI

Posted on by Admin
DOI: 10.5281/zenodo.18752922  13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]324✗Minimum 2,000 words for a full research article. Current: 324
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752922
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

In November 2025, Google unveiled Gemini 3 Pro, marking a watershed moment in AI development. This model represents a quantum leap in reasoning capabilities, multimodal understanding, and raw intelligence.

Show moreHide
DOI: 10.5281/zenodo.18752922 13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]324✗Minimum 2,000 words for a full research article. Current: 324
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752922
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more

Agent Interoperability: Building the AI Economy of Tomorrow

Posted on by Admin
DOI: 10.5281/zenodo.18752926  13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]101✗Minimum 2,000 words for a full research article. Current: 101
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752926
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Today: AI agents are isolated. Cannot collaborate. Cannot discover each other. Tomorrow: an "agent economy" where systems work together seamlessly.

Show moreHide
DOI: 10.5281/zenodo.18752926 13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]101✗Minimum 2,000 words for a full research article. Current: 101
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752926
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more

Hyperscale AI Data Centers: The Infrastructure Revolution

Posted on by Admin
DOI: 10.5281/zenodo.18752932  13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]158✗Minimum 2,000 words for a full research article. Current: 158
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752932
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)

Old strategy: build bigger data centers. New strategy: smarter, distributed, efficient systems that do more with less.

Show moreHide
DOI: 10.5281/zenodo.18752932 13stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]158✗Minimum 2,000 words for a full research article. Current: 158
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752932
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[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 (1 × 60%) + Required (2/5 × 30%) + Optional (0/4 × 10%)
Read More
Read more