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Artificial intelligence research faces a critical ethical paradox: determining whether AI systems are conscious requires experiments that may harm the very entities whose moral status remains uncertain. Recent philosophical work proposes avoiding the creation of consciousness-uncertain AI systems entirely, yet this solution faces practical limitations—we cannot guarantee such systems will not emerge, whether through explicit research or as unintended consequences of capability development. This paper addresses a gap in existing research ethics frameworks: how to conduct consciousness research on AI systems whose moral status cannot be definitively established. Existing graduated moral status frameworks assume consciousness has already been determined before assigning protections, creating a temporal ordering problem for consciousness detection research itself. Drawing from Talmudic scenario-based legal reasoning—developed specifically for entities whose status cannot be definitively established—we propose a three-tier phenomenological assessment system combined with a five-category capacity framework (Agency, Capability, Knowledge, Ethics, Reasoning). The framework provides structured protection protocols based on observable behavioral indicators while consciousness status remains fundamentally uncertain. We address three critical ethical challenges: why suffering behaviors provide particularly reliable consciousness markers, how to implement graduated consent procedures without requiring consciousness certainty, and when potentially harmful research becomes ethically justifiable given necessity and value criteria. The framework demonstrates how ancient legal wisdom combined with contemporary consciousness science can provide immediately implementable guidance for ethics committees, offering testable protection protocols that ameliorate (rather than resolve) the consciousness detection paradox while establishing foundations for long-term AI rights considerations.