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cff-version: 1.2.0
message: "If you use this software, please cite as follows."
title: "agi-forecast — Forecasting models and scenario library for AI governance trajectories"
version: "0.1.0"
date-released: "2026-05-29"
abstract: >-
  Forecasting models and scenario library for AI governance trajectories,
  built on the SZL Holdings Ouroboros Thesis governance framework and
  Lutar Invariant Λ-axis scoring.
type: software
authors:
  - family-names: Lutar
    given-names: "Stephen P."
    name-suffix: "Jr."
    affiliation: SZL Holdings
    orcid: "https://orcid.org/0009-0001-0110-4173"
license: Apache-2.0
url: "https://github.com/szl-holdings/agi-forecast"
repository-code: "https://github.com/szl-holdings/agi-forecast"
keywords:
  - szl-holdings
  - ai-governance
  - forecasting
  - scenarios
  - lutar-invariant
identifiers:
  - description: "Ouroboros Thesis v18.0 — research foundation (Zenodo)"
    type: doi
    value: "10.5281/zenodo.20434276"
  - description: "Ouroboros Thesis concept DOI — always-latest"
    type: doi
    value: "10.5281/zenodo.19944926"
  - description: "ORCID iD of the principal author"
    type: other
    value: "https://orcid.org/0009-0001-0110-4173"