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This paper aims to establish a protocol for maintaining integrity in machine-assisted theory programs through adversarial self-registration.

July 8, 2026Open Access

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Adversarial Self-Registration: A Working Protocol for Keeping a Machine-Assisted Theory Programme Honest

DEDavid EllimanCatholic University of Mozambique

Key Points

This paper aims to establish a protocol for maintaining integrity in machine-assisted theory programs through adversarial self-registration.
Utilizes artifacts from seven disciplines and five case studies.
Includes pre-unblinding amendments and forensic analysis of contributions like dark-energy.
Addresses threats to validity and employs a minimal kit approach.
Demonstrates the impact of severity artifacts on validity.
Highlights specific adjustments made in the protocol to ensure adherence to integrity standards.

Abstract

Adversarial Self-Registration: A Working Protocol for Keeping a Machine-Assisted Theory Programme Honest. Methods paper / severity artifact: seven disciplines, five receipt-backed case studies (honoured 0.005-dex miss, pre-unblinding amendment, e2->-e2 forensic, six-card incl. the internally killed dark-energy branch, failure museum), Mayo severity + the wager, threats to validity, minimal kit. This record is part of the finite-QEC substrate / It-from-Bit publication refresh.

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Adversarial Self-Registration: A Working Protocol for Keeping a Machine-Assisted Theory Programme Honest

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