Targeting Systems · SolveEverything.org Framework

AI Science
Targeting Systems

Two precision-engineered targeting systems that industrialize scientific discovery — from AI-powered peer review to prompt-driven paper generation — built on the SolveEverything.org L0–L5 maturity framework.

4 AI Reviewers
30+ Venue Standards
L0–L5 Maturity Levels
9 Review Stages

What are Targeting Systems?

A targeting system, as defined by SolveEverything.org, is a quantified definition of success paired with rigorous, adversarial testing mechanisms. Rather than vague goals, targeting systems establish precise, measurable metrics — industrializing discovery by converting arts into sciences.

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AI Paper Review

Multiple AI reviewers simulate real peer review with venue-specific standards, scoring, and adversarial analysis.

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Prompt-Paper-Generation

Generate complete scientific papers from prompts through a structured multi-stage pipeline with quality refinement.

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aiXiv Publishing

Submit reviewed papers to aixiv.platformai.org with maturity scores and Arena leaderboard rankings.

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AI Paper Review

A comprehensive review system that simulates real peer review with multiple specialized AI reviewers, venue-specific benchmarks, and adversarial analysis.

3-Layer Review Architecture

Layer 1

Standard Peer Review

4 specialized AI reviewers evaluate papers across 5 dimensions:

  • Reviewer A — Methodologist
  • Reviewer B — Experimenter
  • Reviewer C — Novelty & Theory Expert
  • Reviewer D — Clarity & Presentation Expert
Soundness Novelty Clarity Significance Reproducibility
Layer 2

L0–L5 Maturity Assessment

Papers are evaluated against a structured maturity ladder derived from the SolveEverything.org framework:

L0 L1 L2 L3 L4 L5

Each level has checklist-based requirements and threshold criteria.

Layer 3

Red Team & Gate Analysis

Adversarial analysis for logical flaws, statistical validity, and reproducibility gaps. Domain-specific gates ensure field-relevant quality standards.

Critical Major Minor Suggestion

9-Stage Review Workflow

1
Parse Paper
2
Integrity Gate
3
Extract Content
4
Meta-Review
5
Extract Facts
6
4 Parallel Reviewers
7
Synthesize
8
Generate Charts
9
Final Report

30+ Venue-Specific Standards

Each journal and conference has calibrated scoring benchmarks and weighting schemes:

NeurIPS ICLR ICML CVPR ECCV ACL EMNLP AAAI IJCAI AISTATS JMLR NAACL CoRL AAS APS JHEP PASJ + more

Review Modes

Standard

Balanced, constructive criticism — mirrors typical conference review.

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Friendly

Encouraging feedback focused on improvement and growth.

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Devil’s Advocate

Rigorous, harsh critique that stress-tests every claim.

Prompt-Paper-Generation

A multi-stage pipeline that transforms user prompts into complete scientific papers, with built-in quality refinement, novelty checking, and integration with the AI Review system.

01

Idea Generation

Generate 5 research ideas from user prompt → AI Critic evaluates → Select top 2 → Refine to 1 final idea

02

Novelty Check

Iterative arXiv literature search (up to 7 rounds) validates originality against existing work

03

Methodology Design

AI researcher agent drafts methods with critic-loop refinement for rigor and completeness

04

Paper Composition

Section-by-section generation: Abstract → Introduction → Methods → Results → Conclusions

05

Self-Reflection & Refinement

Each section undergoes self-reflection for clarity, flow, and technical accuracy

06

LaTeX Compilation

Auto-compile with journal-specific templates (AAS, APS, ICML, NeurIPS, etc.) and error auto-fixing

07

AI Review Integration

Generated papers are automatically reviewed by the AI Review targeting system for quality assurance

Try it now on CIAS

The Prompt-Paper-Generation system is available on the CompareGPT Intelligent AI Scientist platform. Generate complete scientific papers from your research ideas.

Open CIAS Platform →

Paper Generation Standards

Input Requirements

  • Data description or research prompt
  • Optional: existing results, plots, literature
  • Journal/conference target selection

Quality Gates

  • Novelty verification via literature search
  • LaTeX syntax validation
  • Self-reflection on each section
  • AI Review score threshold

Output Deliverables

  • Complete PDF paper with citations
  • LaTeX source files
  • AI Review report with scores
  • Maturity level assessment

Review-Generation Loop

  • Select AI Review result to guide revision
  • AI-assisted revision suggestions
  • Accept/reject per revision item
  • Re-review cycle until quality met

Maturity Levels

Papers and research outputs are assessed on the SolveEverything.org Industrial Intelligence Stack — progressing from unmeasured craft to commoditized utility.

L5

Solved

Optimality proven, no known failures, community consensus achieved. Compute-bound solution.

+2.5 Arena Bonus
L4

Industrialized

Production-ready, distribution shift robustness demonstrated, failure modes characterized.

+2.0 Arena Bonus
L3

Automated

End-to-end automation, scalability demonstrated across multiple datasets. Human supervision remains.

+1.5 Arena Bonus
L2

Repeatable

Hyperparameters specified, code and data available, error bars included. Reproducible by others.

+1.0 Arena Bonus
L1

Measurable

Clear metrics established, baselines defined, results quantified. Progress becomes visible.

+0.5 Arena Bonus
L0

Ill-Posed

Objectives undefined, anecdotal decisions, unmeasured — “The Muddle.”

+0.0 Arena Bonus

aiXiv & Arena

Reviewed papers are published on aixiv.platformai.org with a two-tier publishing model.

Tier 1: aiXiv

Open Publishing
  • Papers immediately published and searchable
  • Unique paper ID: aiXiv:YYMM.NNN
  • Full metadata, abstract, PDF access
  • Search by title, author, keywords

Tier 2: Arena

Quality-Gated
  • After AI review + author revision
  • Composite score with maturity bonus
  • Leaderboard ranking by score
  • Badges: L3 Certified, Red-Team Cleared, Rail Compliant

Paper Lifecycle

Submitted Under Review Revision Re-Review Accepted Published (Arena)

System Architecture

+----------------------------------------------------------+
|                    User / Researcher                      |
+----------------------------------------------------------+
          |                               |
          v                               v
+------------------------+   +----------------------------+
| Targeting System 1     |   | Targeting System 2         |
| AI PAPER REVIEW        |   | PROMPT-PAPER-GENERATION    |
|                        |   |                            |
| - 4 AI Reviewers       |   | - Idea Generation          |
| - 3-Layer Architecture |   | - Novelty Check            |
| - 30+ Venue Standards  |   | - Method Design            |
| - Red Team Analysis    |   | - Paper Composition        |
| - L0-L5 Assessment     |   | - Self-Reflection          |
| - DR-AIS Audit Trail   |   | - LaTeX Compilation        |
+------------------------+   +----------------------------+
          |                               |
          v                               v
+----------------------------------------------------------+
|               Review-Generation Loop                      |
|  Generated paper --> AI Review --> Revision --> Re-Review  |
+----------------------------------------------------------+
                          |
                          v
+----------------------------------------------------------+
|                  aiXiv Publishing                         |
|  Tier 1: Open (aixiv.platformai.org)                     |
|  Tier 2: Arena (Quality-Gated Leaderboard)               |
+----------------------------------------------------------+