{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp11_mechanism_context_external20_20260804","cell_id":"invariant_mode_decomposition_design__computer_science","judge_id":"J1","item_assessments":[{"opaque_id":"invariant_mode_decomposition_design__computer_science__C","supported_problem":4,"external_distinctiveness":2,"testability":4,"researchability":4,"evidence_quality":4,"fatal_issue":null},{"opaque_id":"invariant_mode_decomposition_design__computer_science__A","supported_problem":3,"external_distinctiveness":3,"testability":4,"researchability":4,"evidence_quality":4,"fatal_issue":null},{"opaque_id":"invariant_mode_decomposition_design__computer_science__B","supported_problem":3,"external_distinctiveness":3,"testability":4,"researchability":4,"evidence_quality":4,"fatal_issue":null}],"pairwise_comparisons":[{"pair_id":"C_vs_A","left_id":"invariant_mode_decomposition_design__computer_science__C","right_id":"invariant_mode_decomposition_design__computer_science__A","preference":"RIGHT","confidence":"MODERATE","rationale":"C has somewhat stronger direct problem support and an operationally meaningful intervention claim, but its diagnostic core is closely approached by the Kubernetes Jacobian, eigenvalue, modal-participation, and drift pipeline. A retains a clearer externally distinctive increment—pre-threshold retry-cascade warning and action localization—against strong named rivals, with a safer bounded offline and staging test."},{"pair_id":"C_vs_B","left_id":"invariant_mode_decomposition_design__computer_science__C","right_id":"invariant_mode_decomposition_design__computer_science__B","preference":"RIGHT","confidence":"HIGH","rationale":"B offers the stronger remaining research program: it distinguishes asymptotic modes from finite-horizon transient growth, includes conditioning and validity gates, and proposes randomized reversible interventions against two comparators. C is highly testable, but unusually close diagnostic prior art leaves a narrower incremental contribution."},{"pair_id":"A_vs_B","left_id":"invariant_mode_decomposition_design__computer_science__A","right_id":"invariant_mode_decomposition_design__computer_science__B","preference":"RIGHT","confidence":"MODERATE","rationale":"A is well bounded and has a precise retry-storm hypothesis, but B provides the more causally informative experiment and better addresses non-normal transient amplification, ill-conditioned modes, downstream harm, and comparator-controlled intervention effects. B's broader overload claim is less directly established, yet its preregistered staging design makes that uncertainty productively testable."}],"overall_top_choice":"invariant_mode_decomposition_design__computer_science__B","overall_rationale":"B is the most worthwhile candidate after scrutiny because its remaining claim is externally distinct enough to investigate and its next evidence step can directly falsify both detection and intervention benefits. The randomized staging comparison, finite-horizon analysis, model-validity gates, explicit authority, and reversible rollback path give it the best combination of causal informativeness, feasibility, and safety. Its problem-specific advantage remains unproven, but that is a research uncertainty rather than a fatal defect.","blinding_limitations":"The judgment uses only the supplied preserved records and bounded public-web evaluations. The searches were not exhaustive across patents, proprietary systems, paywalled literature, unpublished deployments, or all languages, and differences in retained sources and proposal scope may affect apparent distinctiveness. No treatment identity or earlier outcome was inferred."}