paperlab-publication-opportunity-mining

PaperLab Publication Opportunity Mining

When to Use

USE WHEN: deciding what PaperLab should write next, scanning NeqSim for publication-worthy changes, or converting code and task history into a ranked paper/book roadmap.

Signals to Inspect

Signal	Why it matters
Recent Java classes or tests	Fresh capability or unreported improvement
Existing notebooks and figures	Lowers effort to produce evidence
Changelog and task log entries	Indicates solved problems with reusable context
Unvalidated model claims	Creates validation-paper opportunities
Repeated book sections	May become a standalone review or tutorial paper

Scoring Dimensions

Score candidates from 0 to 5 for:

• novelty,
• NeqSim improvement impact,
• validation data availability,
• benchmark feasibility,
• figure and table richness,
• journal fit,
• book reuse potential.

Output Schema

{
  "opportunities": [
    {
      "slug": "flash_solver_convergence",
      "title": "Flash solver convergence across multiphase envelopes",
      "paper_type": "characterization",
      "readiness": "needs_validation",
      "target_journals": ["computers_chem_eng"],
      "required_evidence": ["benchmark matrix", "reference data", "failure taxonomy"],
      "neqsim_improvement": "adds regression benchmarks and solver diagnostics",
      "score": 22
    }
  ]
}

Pass Criteria

• Each proposed topic has a concrete NeqSim improvement.
• Each topic has a validation or reproducibility path.
• At least one target output is named: paper, chapter, review, benchmark note, or lab.

Safety Rules

• Do not claim novelty without checking prior PaperLab papers and obvious literature.
• Keep private task names and asset tags out of public roadmaps.
• Mark speculative ideas as speculative.