Binary Structural Compliance Gate – Structured Claims Only
A full PDF document is mandatory and becomes the authoritative record.
Structural compliance does not constitute scientific validation or endorsement.
Submission Instructions & Governance
All submissions are evaluated on a binary structural basis:
- ✓ Compliant – all mandatory criteria satisfied
- ✗ Non-Compliant – one or more mandatory criteria not satisfied
There is no conditional or partial compliance. Non-compliant submissions may be revised and resubmitted without prejudice.
Governance Protocol v1.0 – governance.md
Submission Criteria – What Your PDF Must Address
All submissions are evaluated against these 9 structural criteria. The AI pre-check assesses your PDF content directly against each criterion. Criterion 10 is assessed by the Examiner only.
- Clear Core Claim
The submission must state a single, identifiable, operationally testable claim. The claim must not be compound, vague, or metaphorical. If the claim contains multiple independent assertions, or cannot in principle be tested, it does not meet this criterion. - Defined Terms
All key technical terms must be operationally defined and used consistently. Where applicable, the mathematical layer must be separated from the empirical layer. Undefined terminology, circular definitions, or inconsistent usage results in non-compliance. - Mechanism
The submission must propose a physical or structural mechanism that explains why the claim holds. The mechanism must go beyond analogy, metaphor, or mathematical description alone. If the paper explicitly disclaims causality, this criterion fails. - Test Path
The submission must specify an explicit, operationalised test the claim could be subjected to. This means pre-registered criteria, quantitative thresholds, or a specified methodology — not a vague suggestion that testing could theoretically occur. - Falsifiability
There must be a clear, measurable condition that would defeat the claim if observed. An explicit binary falsifier with a defined threshold — not a qualitative gesture or a condition that the framework could absorb through reinterpretation. If it cannot fail, it cannot pass. - Dependency Transparency
The author must explicitly acknowledge their assumptions, observational limitations, interpretive judgements, and any future formalisation requirements. Hidden premises or undeclared dependencies invalidate compliance. - Non-Arbitrary Selection
The analysis must be protected against confirmation bias, cherry-picking, and post-hoc selection. The analysis target must be defined before the search, not selected from it. Pre-registered selection criteria and blind sampling strengthen compliance. - Predictive Capability
The claim must generate at least one novel, testable prediction of undiscovered phenomena. Re-description, classification, or reinterpretation of existing data alone is insufficient. The prediction must be derivable from the claim and independently verifiable. - Reproducibility
An independent reviewer must be able to follow the methodology to replicate the analysis from the description provided. Methodology, data sources, and inclusion criteria must be explicit. Significant reliance on subjective judgement weakens compliance. - Why Is This Claim True? (Examiner Only)
The Examiner evaluates whether the submission answers in structured causal form: “Because X interacts with Y, therefore Z.” This criterion is assessed by the qualified examiner, not by the submitter or the AI pre-check.