The SPECTRA Evidence Stack: A Rule-Specified Neuroaffirmative Framework for Integrating Multi-Source Evidence in...

Psychological assessment of adult neurodivergence relies on multi-informant data that frequently disagree; discrepancies may reflect masking, context-dependent expression, or limited self-insight rather than measurement error.

This paper specifies the SPECTRA Evidence Stack, a rule-based, neuroaffirmative architecture that preserves cross-informant discrepancies as interpretable evidence rather than collapsing them into opaque scores, producing quality flags, convergence profiles, evidence-strength bands, and reason codes.

This is a design specification, not a validation study: no clinical participants were involved. Framework behavior was evaluated on 250 author-generated synthetic records through a four-condition, prespecified rule-configuration comparison and a threshold-perturbation sensitivity analysis. Stochastic generation and score jitter were controlled by a recorded random seed.

With the disclosed code, version, and seed, the reference run was reproducible: mean evidence strength was 0.60 for the full-stack configuration, 0.53 for the no-quality comparator, 0.54 for the no-convergence comparator, and 0.50 for the baseline comparator, with the ordering A > C > B > D preserved in all 12 threshold-perturbation scenarios. These descriptive differences verify the behavior of the four specified configurations; they are not causal estimates of the isolated effects of individual layers. An extended sensitivity analysis covering all 22 reference-configuration parameters (one-at-a-time ±10%, a 1000-sample Latin hypercube joint perturbation of ±20%, and tipping-point sweeps of the band cutoffs) showed that the ordering was preserved in 38/44 single-parameter scenarios but not under joint perturbation (27.8% of samples); the caution cap and the High-band cutoff were the dominant drivers of band assignment. The reference configuration is fully disclosed and independently runnable.

Within the disclosed reference configuration, the SPECTRA Evidence Stack produced reproducible, conditionally assigned evidence-strength outputs that preserved cross-informant discrepancy as interpretable evidence and made uncertainty visible through bands, flags, and reason codes; the ordering of the four rule configurations was preserved in most single-parameter scenarios but not under joint perturbation, and the parameters most influential for band assignment (the caution cap and the High-band cutoff) were identified for priority calibration. Diagnostic accuracy, criterion validity, reliability, and clinical utility are not evaluated here and are reserved for a subsequent clinical validation study, for which a prespecified calibration protocol is now provided.