Tier A Siddhi as Coherence-Control: A Replication-First Scientific Framework

Background: Claims labeled “siddhi” have historically mixed first-person reports, cultural interpretation, and heterogeneous measurement quality. This has made scientific discussion difficult: definitions vary, endpoints are unclear, and replication standards are inconsistent. Objective: To define a Tier A (replication-first) scientific scope for “siddhi” as a measurable, trainable capacity—here operationalized as coherence-control—without invoking extraordinary claims or requiring new physics. Methods: This paper provides (i) operational definitions, (ii) a domain-by-domain endpoint table (behavioral, autonomic, stress-recovery, and sensorimotor robustness), (iii) standardized task protocols with active controls, (iv) preregistration-ready prediction/falsification templates, and (v) a reproducible scoring philosophy emphasizing robustness, coupling validity checks (including time-shuffled negative controls), and retention testing. A minimal BUFT (Bijay Unified Field Theory) operational layer is included only as a notation system (e.g., X, C, and ΣK) mapping to measurable variables; all claims remain testable within standard physiology and behavioral science. No primary human data are reported. Results: No primary results are presented. The output of this work is a testable program: preregistration templates, minimum instrumentation requirements, standardized endpoints, and a reproducible analysis pipeline specification designed to minimize analysis drift. Conclusions: A Tier A operationalization of “siddhi” as coherence-control is scientifically tractable and falsifiable. If validated, it would establish a narrow, conservative bridge between contemplative training and measurable improvements in dynamic stability, recovery kinetics, and multi-system coupling—without overclaiming. Significance: This paper reframes “siddhi” from an assertion to a replication program. The Tier A approach makes the topic testable under modern standards (preregistration, active controls, retention, transparent QC, and reproducible pipelines), allowing the field to converge on what is real, what is not, and what remains undecidable under current measurement limits.